Overview About Big Data and Hadoop - Part 2

This post is a continuation from previous post. Still about big data and hadoop from The Executive's Guide To Big Data & Apache Hadoop by Robert D. Schneider, this post tell us about the story behind hadoop and end with things to loop up when evaluating hadoop technology.

Distributed Processing Methodologies

In the past, organizations that wanted to work with large information sets would have needed to:

• Acquire very powerful servers, each sporting very fast processors and lots of memory 
• Stage massive amounts of high-end, often-proprietary storage 
• License an expensive operating system, a RDBMS, business intelligence, and other software
• Hire highly skilled consultants to make all of this work 
• Budget lots of time and money

Fortunately, several distinct but interrelated technology industry trends have made it possible to apply fresh strategies to work with all this information:

• Commodity hardware
• Distributed file systems
• Open source operating systems, databases, and other infrastructure
• Significantly cheaper storage
• Widespread adoption of interoperable Application Programming Interfaces (APIs)

Today, there’s an intriguing collection of powerful distributed processing methodologies to help derive value from Big Data.

In a nutshell, these distributed processing methodologies are constructed on the proven foundation of ‘Divide and Conquer’: it’s much faster to break a massive task into smaller chunks and process them in parallel. There’s a long history of this style of computing, dating all the way back to functional programming paradigms like LISP in the 1960s.

Given how much information it must manage, Google has long been heavily reliant on these tactics. In 2004, Google published a white paper that described their thinking on parallel processing of large quantities of data, which they labeled “MapReduce”. The white paper was conceptual in that it didn’t spell out the implementation technologies per se. Google summed up MapReduce as follows:

“MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key.”

MapReduce was proven to be one of the most effective techniques for conducting batch-based analytics on the gargantuan amounts of raw data generated by web search and crawling before organizations expanded their use of MapReduce to additional scenarios.

Rather than referring to a single tactic, MapReduce is actually a collection of complementary processes and strategies that begins by pairing commoditized hardware and software with specialized underlying file systems. Computational tasks are then directly performed on the data wherever it happens to reside, rather than the previous practices of first copying and aggregating raw data into a single repository before processing it. These older practices simply won’t scale when the amount of data expands beyond terabytes. Instead, MapReduce’s innovative thinking means that rather than laboriously moving huge volumes of raw data across a network, only code is sent over the network.

MapReduce was, and continues to be, a superb strategy for the problem that it was originally designed to solve: how to conduct batch analysis on the massive quantities of data generated by users running searches and visiting web sites. The concepts behind MapReduce have also served as the inspiration for an ever-expanding collection of novel parallel processing computational frameworks aimed at a variety of use cases, such as streaming analysis, interactive querying, integrating SQL with machine learning, and so on. While not all of these new approaches will achieve the same level of traction as the popular and still-growing batch-oriented MapReduce, many are being used to solve interesting challenges and drive new applications.

Conveniently, each of these methodologies shields software developers from the thorny challenges of distributed, parallel processing. But as Robert D. Schneider described earlier, Google’s MapReduce paper didn’t dictate exactly what technologies should be used to implement its architecture. This means that unless you worked for Google, it’s unlikely that you had the time, money, or people to design, develop, and maintain your own, site-specific set of all of the necessary components for systems of this sophistication. After all, it’s doubtful that you built your own proprietary operating system, relational database management system, or Web server.

Thus, there was a need for a complete, standardized, end-to-end solution suitable for enterprises seeking to apply the full assortment of modern, distributed processing techniques to help extract value from reams of Big Data. This is where Hadoop comes in.

Hadoop

Around the same time that Google was publishing the MapReduce paper, two engineers - Doug Cutting and Mike Cafarella - were busily working on their own web crawling technology named Nutch. After reading Google’s research, they quickly adjusted their efforts and set out to create the foundations of what would later be known as Hadoop. Eventually, Cutting joined Yahoo! where the Hadoop technology was expanded further. As Hadoop grew in sophistication, Yahoo! extended its usage into additional internal applications. In early 2008, the Apache Software Foundation (ASF) promoted Hadoop into a top-level open source project.

Simply stated, Hadoop is a comprehensive software platform that executes distributed data processing techniques. It’s implemented in several distinct, specialized modules:

• Storage, principally employing the Hadoop File System (HDFS) although other more robust alternatives are available as well 
• Resource management and scheduling for computational tasks 
• Distributed processing programming model based on MapReduce 
• Common utilities and software libraries necessary for the entire Hadoop platform

Hadoop has broad applicability across all industries.

Enterprises have responded enthusiastically to Hadoop. Table 3 below illustrates just a few examples of how Hadoop is being used in production today. 

Selecting your Hadoop infrastructure is a vital IT decision that will affect the entire organization for years to come, in ways that you can’t visualize now. This is particularly true since we’re only at the dawn of Big Data in the enterprise. Hadoop is no longer an “esoteric”, lab-oriented technology; instead, it’s becoming mainline, it’s continually evolving, and it must be integrated into your enterprise. Selecting a Hadoop implementation requires the same level of attention and devotion as your organization expends when choosing other critical core technologies, such as application servers, storage, and databases. You can expect your Hadoop environment to be subject to the same requirements as the rest of your IT asset portfolio, including:

• Service Level Agreements (SLAs)
• Data protection
• Security
• Integration with other applications

Checklist: Ten Things to Look for When Evaluating Hadoop Technology

1. Look for solutions that support open source and ecosystem components that support Hadoop API’s. It’s wise to make sure API’s are open to avoid lock-in.

2. Interoperate with existing applications. One way to magnify the potential of your Big Data efforts is to enable your full portfolio of enterprise applications to work with all of the information you’re storing in Hadoop.

3. Examine the ease of migrating data into and out of Hadoop. By mounting your Hadoop cluster as an NFS volume, applications can load data directly into Hadoop and then gain real-time access to Hadoop’s results. This approach also increases usability by supporting multiple concurrent random access readers and writers.

4. Use the same hardware for OLTP and analytics. It’s rare for an organization to maintain duplicate hardware and storage environments for different tasks. This requires a high-performance, low-latency solution that doesn’t get bogged down with time-consuming tasks such as garbage collection or compactions. Reducing the overhead of the disk footprint and related I/O tasks helps speed things up and increases the likelihood of efficient execution of different types of processes on the same servers.

5. Focus on scalability. In its early days, Hadoop was primarily used for offline analysis. Although this was an important responsibility, instant responses weren’t generally viewed as essential. Since Hadoop is now driving many more types of use cases, today’s Hadoop workloads are highly variable. This means that your platform must be capable of gracefully and transparently allocating additional resources on an as-needed basis without imposing excessive administrative and operational burdens.

6. Ability to provide real-time insights on newly loaded data. Hadoop’s original use case was to crawl and index the Web. But today – when properly implemented – Hadoop can deliver instantaneous understanding of live data, but only if fresh information is immediately available for analysis.

7. A completely integrated solution. Your database architects, operations staff, and developers should focus on their primary tasks, instead of trying to install, configure, and maintain all of the components in the Hadoop ecosystem.

8. Safeguard data via multiple techniques. Your Hadoop platform should facilitate duplicating both data and metadata across multiple servers using practices such as replication and mirroring. In the event of an outage on a particular node you should be able to immediately recover data from where it has been replicated in the cluster. This not only fosters business continuity, it also presents the option of offering read-only access to information that’s been replicated to other nodes. Snapshots - which should be available for both files and tables - provide point-in-time recovery capabilities in the event of a user or application error.

9. Offer high availability. Hadoop is now a critical enterprise technology infrastructure. Like other enterprise-wide fundamental software assets, it should be possible to upgrade your Hadoop environment without shutting it down. Furthermore, your core Hadoop system should be isolated from user tasks so that runaway jobs can’t degrade or even bring down your entire cluster.

10. Complete administrative tooling and comprehensive security. It should be easy for your operational staff to maintain your Hadoop landscape, with minimal amounts of manual procedures. Self-tuning is an excellent way that a given Hadoop environment can reduce administrative overhead, and it should also be easy for you to incorporate your existing security infrastructure into Hadoop.

Overview About Big Data and Hadoop - Part 1

Big Data has come to Indonesia. One of my customer ask about it. I don't know if the needs has come or only temporary joy from outside. Still, I think I need to improve my knowledge about Big Data and Hadoop. I found that the book titled : The Executive's Guide To Big Data & Apache Hadoop by Robert D. Schneider is very good and insightful. This book contained everything you need to understand and get started with Big Data and Hadoop. You can find the eBook free in Google, but if you need something more summarize please read my summary below.

Introducing Big Data

Big Data has the potential to transform the way you run your organization. When used properly it will create new insights and more effective ways of doing business, such as:

• How you design and deliver your products to the market
• How your customers find and interact with you
• Your competitive strengths and weaknesses
• Procedures you can put to work to boost the bottom line

What Turns Plain Old Data into Big Data?

From Robert D. Schneider perspective, organizations that are actively working with Big Data have each of the following five traits in comparison to those who don’t:

1. Larger amounts of information
2. More types of data
3. Data that’s generated by more sources
4. Data that’s retained for longer periods
5. Data that’s utilized by more types of applications

1. Larger Amounts of Information
Enterprises are capturing, storing, managing, and using more data than ever before. Generally, these events aren’t confined to a single organization; they’re happening everywhere: 
On average over 500 million Tweets occur every day 
World-wide there are over 1.1 million credit card transactions every second 
There are almost 40,000 ad auctions per second on Google AdWords 
On average 4.5 billion “likes” occur on Facebook every day

Comparing Database Sizes

2. More Types of Data
Structured data – regularly generated by enterprise applications and amassed in relational databases – is usually clearly defined and straightforward to work with. On the other hand, enterprises are now interacting with enormous amounts of unstructured – or semi-structured – information, such as:

• Clickstreams and logs from websites 
• Photos 
• Video 
• Audio 
• XML documents 
• Freeform blocks of text such as email messages, Tweets, and product reviews

3. Generated by More Sources
Enterprise applications continue to produce transactional and web data, but there are many new conduits for generating information, including: 

• Smartphones 
• Medical devices 
• Sensors
• GPS location data 
• Machine-to-machine, streaming communication

4. Retained for Longer Periods
Government regulations, industry standards, company policies, and user expectations are all contributing to enterprises keeping their data for lengthier amounts of time. Many IT leaders also recognize that there are likely to be future use cases that will be able to profit from historical information, so carelessly throwing data away isn’t a sound business strategy. However, hoarding vast and continually growing amounts of information in core application storage is prohibitively expensive. Instead, migrating information to Hadoop is significantly less costly, plus Hadoop is capable of handling a much bigger variety of data.

5. Utilized by More Types of Applications
Faced with a flood of new information, many enterprises are following a “grab the data first, and then figure out what to do with it later” approach. This means that there are countless new applications being developed to work with all of this diverse information. Such new applications are widely varied, yet must satisfy requirements such as bigger transaction loads, faster speeds, and enormous workload variability.

Big Data is also shaking up the analytics landscape. Structured data analysis has historically been the prime player, since it works well with traditional relational database-hosted information. However, driven by Big Data, unstructured information analysis is quickly becoming equally important. Several new techniques work with data from manifold sources such as:

• Blogs 
• Facebook 
• Twitter 
• Web traffic logs 
• Text messages 
• Yelp reviews
• Support desk calls 
• Call center calls

Implications of Not Handling Big Data Properly

Failing to keep pace with the immense data volumes, mushrooming number of information sources and categories, longer data retention periods, and expanding suite of data-hungry applications has impeded many Big Data plans, and is resulting in:

• Delayed or faulty insights 
• An inability to detect and manage risk 
• Diminished revenue 
• Increased cost 
• Opportunity costs of missing new applications along with operational use of data 
• A weakened competitive position

Checklist: How to Tell When Big Data Has Arrived

1. You’re getting overwhelmed with raw data from mobile or medical devices, sensors, and/or machine-to-machine communications. Additionally, it’s likely that you’re so busy simply capturing this data that you haven’t yet found a good use for it.

2. You belatedly discover that people are having conversations about your company on Twitter. Sadly, not all of this dialogue is positive.

3. You’re keeping track of a lot more valued information from many more sources, for longer periods of time. You realize that maintaining such extensive amounts of historical data might present new opportunities for deeper awareness into your business.

4. You have lots of silos of data, but can’t figure out how to use them together. You may already be deriving some advantages from limited, standalone analysis, but you know that the whole is greater than the sum of the parts.

5. Your internal users – such as data analysts – are clamoring for new solutions to interact with all this data. They may already be using one-off analysis tools such as spreadsheets, but these ad-hoc approaches don’t go nearly far enough.

6. Your organization seeks to make real-time business decisions based on newly acquired information. These determinations have the potential to significantly impact daily operations.

7. You’ve heard rumors (or read articles) about how your competitors are using Big Data to gain an edge, and you fear being left behind.

8. You’re buying lots of additional storage each year. These supplementary resources are expensive, yet you’re not putting all of this extra data to work.

9. You’ve implemented – either willingly or by necessity – new information management technologies, often from startups or other cutting-edge vendors. However, many of these new solutions are operating in isolation from the rest of your IT portfolio.


Click Here For Part 2

RAID Overview and Types

If you've ever looked into purchasing a NAS device or server, particularly for a small business, you've no doubt come across the term "RAID." RAID stands for Redundant Array of Inexpensive (or sometimes "Independent") Disks. In general, a RAID-enabled system uses two or more hard disks to improve the performance or provide some level of fault tolerance for a machine—typically a NAS or server. Fault tolerance simply means providing a safety net for failed hardware by ensuring that the machine with the failed component, usually a hard drive, can still operate. Fault tolerance lessens interruptions in productivity, and it also decreases the chance of data loss.

The way in which you configure that fault tolerance depends on the RAID level you set up. RAID levels depend on how many disks you have in a storage device, how critical drive failover and recovery is to your data needs, and how important it is to maximize performance. A business will generally find it more urgent to keep data intact in case of hardware failure than, for example, a home user will. Different RAID levels represent different configurations aimed at providing different balances between performance optimization and data protection.

RAID Overview
RAID is traditionally implemented in businesses and organizations where disk fault tolerance and optimized performance are must-haves, not luxuries. Servers and NASes in business datacenters typically have a RAID controller—a piece of hardware that controls the array of disks. These systems feature multiple SSD or SATA drives, depending on the RAID configuration. Because of the increased storage demands of consumers, home NAS devices also support RAID. Home, prosumer, and small business NASes are increasingly shipping with two or more disk drive bays so that users can leverage the power of RAID just like an enterprise can.

Software RAID means you can setup RAID without need for a dedicated hardware RAID controller. The RAID capability is inherent in the operating system. Windows 8's Storage Spaces feature and Windows 7 (Pro and Ultimate editions) have built-in support for RAID. You can set up a single disk with two partitions: one to boot from and the other for data storage and have the data parition mirrored.

This type of RAID is available in other operating systems as well, including OS X Server, Linux, and Windows Servers. Since this type of RAID already comes as a feature in the OS, the price can't be beat. Software RAID can also comprise virtual RAID solutions offered by vendors such as Dot Hill to deliver powerful host-based virtual RAID adapters. That's a solution more tailored to enterprise networks, however.

Which RAID Is Right for Me?
As mentioned, there are several RAID levels, and the one you choose depends on whether you are using RAID for performance or fault tolerance (or both). It also matters whether you have hardware or software RAID, because software supports fewer levels than hardware-based RAID. In the case of hardware RAID, the type of controller you have matters, too. Different controllers support different levels of RAID and also dictate the kinds of disks you can use in an array: SAS, SATA or SSD.

Here's the rundown on popular RAID levels:

RAID 0 is used to boost a server's performance. It's also known as "disk striping." With RAID 0, data is written across multiple disks. This means the work that the computer is doing is handled by multiple disks rather than just one, increasing performance because multiple drives are reading and writing data, improving disk I/O. A minimum of two disks is required. Both software and hardware RAID support RAID 0, as do most controllers. The downside is that there is no fault tolerance. If one disk fails, then that affects the entire array and the chances for data loss or corruption increases.

RAID 1 is a fault-tolerance configuration known as "disk mirroring." With RAID 1, data is copied seamlessly and simultaneously, from one disk to another, creating a replica, or mirror. If one disk gets fried, the other can keep working. It's the simplest way to implement fault tolerance and it's relatively low cost.

The downside is that RAID 1 causes a slight drag on performance. RAID 1 can be implemented through either software or hardware. A minimum of two disks is required for RAID 1 hardware implementations. With software RAID 1, instead of two physical disks, data can be mirrored between volumes on a single disk. One additional point to remember is that RAID 1 cuts total disk capacity in half: If a server with two 1TB drives is configured with RAID 1, then total storage capacity will be 1TB not 2TB.

RAID 5 is by far the most common RAID configuration for business servers and enterprise NAS devices. This RAID level provides better performance than mirroring as well as fault tolerance. With RAID 5, data and parity (which is additional data used for recovery) are striped across three or more disks. If a disk gets an error or starts to fail, data is recreated from this distributed data and parity block— seamlessly and automatically. Essentially, the system is still operational even when one disk kicks the bucket and until you can replace the failed drive. Another benefit of RAID 5 is that it allows many NAS and server drives to be "hot-swappable" meaning in case a drive in the array fails, that drive can be swapped with a new drive without shutting down the server or NAS and without having to interrupt users who may be accessing the server or NAS. It's a great solution for fault tolerance because as drives fail (and they eventually will), the data can be rebuilt to new disks as failing disks are replaced. The downside to RAID 5 is the performance hit to servers that perform a lot of write operations. For example, with RAID 5 on a server that has a database that many employees access in a workday, there could be noticeable lag.

RAID 6 is also used frequently in enterprises. It's identical to RAID 5, except it's an even more robust solution because it uses one more parity block than RAID 5. You can have two disks die and still have a system be operational.

RAID 10 is a combination of RAID 1 and 0 and is often denoted as RAID 1+0. It combines the mirroring of RAID 1 with the striping of RAID 0. It's the RAID level that gives the best performance, but it is also costly, requiring twice as many disks as other RAID levels, for a minimum of four. This is the RAID level ideal for highly utilized database servers or any server that's performing many write operations. RAID 10 can be implemented as hardware or software, but the general consensus is that many of the performance advantages are lost when you use software RAID 10.

Source 1 : PC Mag
Source 2 : Wikipedia

SAN vs NAS - Overview

...Network Attached Storage (NAS)...

Wikipedia
Network-attached storage (NAS) is file-level computer data storage server connected to a computer network providing data access to a heterogeneous group of clients. NAS not only operates as a file server, but is specialized for this task either by its hardware, software, or configuration of those elements. NAS is often manufactured as a computer appliance – a specialized computer built from the ground up for storing and serving files – rather than simply a general purpose computer being used for the role.

Ecei
Network Attached Storage (NAS) devices are storage arrays or gateways that support file-based storage protocols such as NFS and CiFS, and are typically connected via an IP network. These file-based protocols provide clients shared access to storage resources. This centralization of shared storage resources reduces management complexity, minimizes stranded disk capacity, improves storage utilization rates and eliminates file server sprawl.

Benefits :

• NAS devices typically leverage existing IP networks for connectivity, enabling companies to reduce the price of entry for access to shared storage.
• The RAID and clustering capabilities inherent to modern enterprise NAS devices offer greatly improved availability when compared with traditional direct attached storage.
• Because NAS devices control the file system, they offer increased flexibility when using advanced storage functionality such as snapshots.
• With 10GE connectivity, NAS devices can offer performance on par with many currently installed fibre channel SANs

...Storage Area Network (SAN)...

Wikipedia
A storage area network (SAN) is a dedicated network that provides access to consolidated, block level data storage. SANs are primarily used to enhance storage devices, such as disk arrays, tape libraries, and optical jukeboxes, accessible to servers so that the devices appear like locally attached devices to the operating system. A SAN typically has its own network of storage devices that are generally not accessible through the local area network (LAN) by other devices. The cost and complexity of SANs dropped in the early 2000s to levels allowing wider adoption across both enterprise and small to medium sized business environments.

A SAN does not provide file abstraction, only block-level operations. However, file systems built on top of SANs do provide file-level access, and are known as SAN filesystems or shared disk file systems.

Ecei
Storage Area Networks or sometimes referred to as SAN, are a separate computer network typically based on a fabric of fiber channel switches and hubs, connecting storage subsystems to a heterogeneous set of servers on an any-server-to-any-server basis. A SAN enables direct storage-to-storage interconnectivity and lends itself to taking advantage of new types of clustering technology.

Benefits :

• Promotes high availability
• Improves data storage management and reduces costs
• Enables efficient hardware deployment and utilization
• Improves data backup efficiency and accessibility
• Enables storage virtualization

...Differences...

About

• SAN vs NAS - What Is the Difference?Both Storage Area Networks (SANs) and Network Attached Storage (NAS) provide networked storage solutions. 
• A NAS is a single storage device that operate on data files, while a SAN is a local network of multiple devices that operate on disk blocks.
• A SAN commonly utilizes Fibre Channel interconnects. A NAS typically makes Ethernet and TCP/IP connections.

The administrator of a home or small business network can connect one NAS device to their LAN. The NAS maintains its own IP address comparable to computer and other TCP/IP devices. Using a software program that normally is provided together with the NAS hardware, a network administrator can set up automatic or manual backups and file copies between the NAS and all other connected devices. The NAS holds many gigabytes of data, up to a few terabytes. Administrators add more storage capacity to their network by installing additional NAS devices, although each NAS operates independently.

Administrators of larger enterprise networks may require many terabytes of centralized file storage or very high-speed file transfer operations. Where installing an army of many NAS devices is not a practical option, administrators can instead install a single SAN containing a high-performance disk array to provide the needed scalability and performance. Administrators require specialized knowledge and training to configure and maintain SANs.

Renungan Kristen : RICH / Kaya

RICH - Lukas 19:11-27

R = Resources | Yang Dimiliki
I = Impact & Influence | Berdampak & Berpengaruh
C = Contentment | Kepuasan, Merasa Cukup
H = Humility | Kerendahan Hati

...

Apa artinya rich atau kaya?

...

R = Resources | Yang Dimiliki

Amsal 22:1
Nama baik lebih berharga daripada kekayaan besar, dikasihi orang lebih baik daripada perak dan emas.

Amsal 3:16
Umur paniang ada di tangan kanannya, di tangan kirinya kekayaan dan kehormatan.


I = Impact & Influence | Berdampak & Berpengaruh

Pengkhotbah 9:16
Kataku: "Hikmat lebih baik daripada keperkasaan, tetapi hikmat orang miskin dihina dan perkataannya tidak didengar orang."

Lukas 19:21-23
Sebab aku takut akan tuan, karena tuan adalah manusia yang keras; tuan mengambil apa yang tidak pernah tuan taruh dan tuan menuai apa yang tidak tuan tabur.
Katanya kepada hamba itu: Hai hamba yang jahat, aku akan menghakimi engkau menurut perkataanmu sendiri. Engkau sudah tahu bahwa aku adalah orang yang keras, yang mengambil apa yang tidak pernah aku taruh dan menuai apa yang tidak aku tabur.
Jika demikian, mengapa uangku itu tidak kau berikan kepada orang yang menjalankan uang? Maka sekembaliku aku dapat mengambilnya serta dengan bunganya.

C = Contentment | Kepuasan, Merasa Cukup

Pengkhotbah 5:10
Siapa yang mencintai uang tidak akan puas dengan uang, dan siapa mencintai kekayaan tidak akan puas dengan penghasilannya. Inipun sia-sia.

1 Timotius 6:6-10
Memang ibadah itu kalau disertai rasa cukup, memberi keuntungan besar.
Sebab kita tidak membawa sesuatu apa ke dalam dunia dan kitapun tidak dapat membawa apa-apa ke luar.
Asal ada makanan dan pakaian, cukuplah.
Tetapi mereka yang ingin kaya terjatuh ke dalam pencobaan, ke dalam jerat dan ke dalam berbagai-bagai nafsu yang hampa dan yang mencelakakan, yang menenggelamkan manusia ke dalam keruntuhan dan kebinasaan.
Karena akar segala kejahatan ialah cinta uang. Sebab oleh memburu uanglah beberapa orang telah menyimpang dari iman dan menyiksa dirinya dengan berbagai-bagai duka.

Filipi 4:11-13
Kukatakan ini bukanlah karena kekurangan, sebab aku telah belajar mencukupkan diri dalam segala keadaan.
Aku tahu apa itu kekurangan dan aku tahu apa itu kelimpahan. Dalam segala hal dan dalam segala perkara tidak ada sesuatu yang merupakan rahasia bagiku; baik dalam hal kenyang, maupun dalam hal kelaparan, baik dalam hal kelimpahan maupun dalam hal kekurangan.
Segala perkara dapat kutanggung di dalam Dia yang memberi kekuatan kepadaku.

H = Humility | Kerendahan Hati

1 Timotius 6:17
Peringatkanlah kepada orang-orang kaya di dunia ini agar mereka jangan tinggi hati dan jangan berharap pada sesuatu yang tak tentu seperti kekayaan, melainkan kepada Allah yang dalam kekayaan-Nya memberikan kepada kita segala sesuatu untuk dinikmati.

Ulangan 8:17-18
Maka janganlah kaukatakan dalam hatimu: Kekuasaanku dan kekuatan tangankulah yang membuat aku memperoleh kekayaan ini.
Tetapi haruslah engkau ingat kepada TUHAN, Allahmu, sebab Dialah yang memberikan kepadamu kekuatan untuk memperoleh kekayaan, dengan maksud meneguhkan perjanjian yang diikrarkan-Nya dengan sumpah kepada nenek moyangmu, seperti sekarang ini.

Amsal 10:22
Berkat Tuhanlah yang menjadikan kaya, susah payah tidak akan menambahinya.

...

Apa yang Tuhan inginkan dari kita?

• Kekayaan berasal dari Tuhan.
• Tuhan menginginkan kita untuk berkembang dan menggunakannya untuk berdampak bagi orang lain.
• Tuhan menginginkan kita untuk mengucap syukur atas segala berkat dan karuniannya.

Sifat Kaya?

• Etika menjadi dasar
• Berintegritas
• Bertanggung jawab
• Hormat (menghargai)
• Berusaha
• Tepat waktu

Sumber : Wiwie Yudiantyo (CEO - PT AGIT Monitise - Via Email Blast 11 Juli 2014)

Choices and Decisions

One : Do not promise when you're happy.

Two : When you are angry, do not respond.

Three : Do not decide when you are sad.

Some people decide something when they are under circumstances that the brain and the heart cannot synergy. Promise, anger, or decision sometimes made in the wrong time and at the wrong place. We have to control our body, mind and heart in order to control our life. The most bad control example is give up. 

Before you give up, think of the reason why you held on for so long.

Listen to your own voice and your own soul. Too many people listen to the noise of the world instead of themselves. 

We cannot think clearly and decide something unwisely about our choice because we pushed by the conditions, not by our own reason. The best time to decide is after through the step of summarizing and analyzing. Summarize what we have been through. Analyze the reason why we held on for long. 

Sometimes you give on someone, not because you don't care but because they don't.

Never waste your feelings on someone who doesn't value them.

When it come to relationship, what we important is value. Value is created based on the realization of feelings. When one / both of the couple give less value, wrong value, meaningless value, it is a sign when they have to consider their relationship.

There's a difference between giving up and moving on.

I know that it is different when we prefer to moving on rather than giving up. What is the differences? Simple, give up is stop doing something that you do regularly, move on mean to stop discussing or doing something and begin discussing or doing something different. .

Sometimes good people make bad choices. It doesn't mean they are bad people, it means they are human. 

 
And the most important thing don't blame ourselves. Learn the choices and remember that there are cost and responsibility for every decision we made. The most important thing, just be your self and don't forget to ask for God's guidance for every decision you will make. Have a nice day. God bless.

Mengenal Generasi Y

Beberapa waktu lalu, seseorang bercerita tentang karirnya. Bukan spesifik tentang karirnya tetapi bagaimana dia menghadapi tantangan mengembangkan bisnis perusahaan tempat dia bekerja dalam mengejar pangsa pasar generasi Y. Lalu apakah itu generasi Y? Pada waktu itu saya manggut-manggut saja seolah mengerti, namun setelah googling saya mengerti lewat artikel dari manajemenppm oleh ibu Octa.

Dengan membaca artikel tersebut, saya mengetahuai bahwa saya ternyata termasuk dalam kategori generasi Y, yang mana saya merupakan seorang yang terlahir pada tahun 1990. Betul sekali yang dikatakan ibu Octa lewat artikelnya bahwa kita yang termasuk gen Y lebih terbuka pada politik dan ekonomi yang tentunya dipengaruhi perkembangan teknologi, contohnya pemilu kemarin.

Artikel juga menjelaskan hal - hal lain dalam kehidupan pekerjaan. Saya cederung sangat memanfaatkan teknologi yang ada seperti internet dalam pekerjaan, bukan sekedar karena saya bekerja sebagai konsultan IT. Hal lainnya yang berkaitan dengan gen Y adalah saya sangat menyukai pekerjaan kelompok. Ini didukung oleh kepribadian saya yang kholeris, dimana manajemen dan organisasi adalah sesuatu yang terkandung didalamnya. Dalam menjalani karir, saya suka mengembangkan diri saya dan berharap hal tersebut didukung oleh perusahaan tempat saya berkarya. Untuk itu saya sangat terbuka pada atasan agar segala sesuatunya berjalan lancar, baik untuk saya pribadi maupun perusahaan.

Silahkan baca artikel dibawah ini, agar wawasan kita tentang generasi Y bertambah. 
Selamat membaca.

Mengenal Siapa Itu Generasi Y?

Generasi Y, yang biasanya juga disebut sebagai generasi millenium, merupakan generasi yang muncul setelah Generasi X. Ungkapan Generasi Y itu mulai dipakai pada editorial koran besar di Amerika Serikat bulan Agustus tahun 1993.

Pada saat itu editor koran tersebut sedang membahas para remaja yang pada saat itu baru berumur 12–13 tahun, namun memiliki perilaku yang berbeda dengan Generasi X. Kemudian perusahaan-perusahaan pada saat itu mulai mengelompokan anak-anak yang lahir setelah tahun 1980-an sebagai anak-anak Generasi Y.

Hingga saat ini, apabila kita membaca berbagai literatur yang mendiskusikan tentang Generasi Y, tidak pernah ada suatu kesepakatan kapan generasi ini dimulai. Sebahagian literatur menetapkan bahwa mereka adalah generasi yang lahir di awal tahun 1980-an, namun banyak juga literatur yang menetapkan bahwa generasi ini lahir di awal, di tengah bahkan di akhir 1990-an.

Di berbagai belahan bumi pun, belum ada kesepakatan tentang Generasi Y ini. Di Australia, para ahli belum menyepakati kapan persisnya Generasi Y ini muncul dan kapan pula tepatnya generasi ini berakhir atau “cutoff”. Pemerintah Australia sendiri melalui Australian Bureau of Statistics, menetapkan 1982–2000 sebagai masa Generasi Y.

Lain lagi dengan Canada, hampir semua ahli sepakat kalau Generasi Y lahir tahun 1982, dan periode akhir dari Generasi Y ini pertengahan tahun 1990-an atau 2000. Walau pun demikian di antara semua perbedaan, hampir semua literatur sepakat bahwa sebahagaian besar Generasi Y, lahir diantara tahun 1980-an hingga 1990-an.

Semua literatur juga sepakat bahwa sebahagian besar orang tua Generasi Y adalah generasi baby boomers, yang mempunyai kecenderungan untuk memiliki keluarga kecil, sehingga biasanya mereka hanya mempunyai kakak atau adik, tidak lebih dari 3 orang. Walaupun mereka tidak suka, Generasi Y dianggap sebagai suksesor dari Generasi X.

Mengapa Mereka Berbeda?

Apabila kita memperhatikan perilaku atau karakteristik Generasi Y di setiap daerah Indonesia, maka kita akan melihat karakteristik yang berbeda-beda, tergantung di mana ia dibesarkan, strata ekonomi dan sosial keluarganya. Namun secara keseluruhan, kita dapat melihat bahwa Generasi Y itu sangat terbuka pola komunikasinya dibandingkan generasi-generasi sebelumnya.

Mereka juga pemakai media sosial yang fanatik dan kehidupannya sangat terpengaruh dengan perkembangan teknologi. Kita juga bisa melihat di setiap provinsi, bahwa mereka lebih terbuka dengan pandangan politik dan ekonominya sehingga mereka terlihat sangat reaktif terhadap perubahan lingkungan yang terjadi di sekelilingnya.

Dari pengalaman pribadi sebagai senior consultant di PPM Manajemen, saya melihat bahwa Generasi Y itu terlihat lebih concern terhadap ‘wealth’ daripada generasi-generasi sebelumnya terutama generasi saya, Generasi Baby Boomers.

Banyak di antara mereka yang sudah membuat rencana apa saja yang mereka inginkan pada saat mereka baru berumur 20-an. Namun definisi mereka tentang ‘wealth’ bukan mengacu kepada kekayaan material saja. Buat mereka hubungan keluarga dan pertemanan juga dianggap sebagai bagian dari ‘wealth’ yang diinginkan.

Saya sering bertemu dengan Generasi Y, yang pindah perusahaan karena perusahaan menuntut mereka bekerja lebih dari 12 jam, sehingga mereka merasa tidak diberi kesempatan untuk membangun kehidupan keluarga atau sosial lainnya, seperti apa yang mereka inginkan. Bahkan, beberapa di antara mereka memutuskan pindah ke perusahaan dengan imbal jasa yang lebih kecil, karena mereka ingin mempunyai waktu yang lebih banyak buat keluarga.

Namun untuk memliliki pandangan secara akurat tentang Generasi Y ini, ada baiknya kita melihat pendapat para ahli yang kompeten. Secara internasional ada berbagai pendapat yang paling populer mengenal Generasi Y.

Pendapat pertama, mengenai generasi Y yang perlu diperhatikan adalah pendapat penulis William Strauss dan Neil Howe yang mencoba mendefinisikan generasi-generasi yang ada di Amerika dalam buku mereka Generations: The History of America’s Future, 1584 to 2069 (1991).

Teori mereka tentang generasi ini banyak diambil oleh berbagai penulis jurnal dan buku yang membahas masalah-masalah antar generasi. Howe and Strauss selalu memakai terminologi Generasi Millenium bagi Generasi Y, karena mereka yakin bahwa anggota Generasi Y sangat tidak suka apabila mereka diasosiasikan dengan Generasi X.

William Strauss dan Neil Howe juga menganggap Generasi Y merupakan generasi yang istimewa. Dalam buku mereka yang berjudul The Fourth Turning, yang ditulis pada tahun 1997, mereka banyak menuliskan keyakinan mereka ini. Keduanya, berpendapat bahwa sejarah modern itu akan selalu berulang sendiri setiap 4 siklus sosial, yang setiap siklus kurang lebih memakan waktu 80 sampai 100 tahun.

Dalam buku tersebut penulis juga meyakini bahwa 4 siklus sosial itu selalu terjadi dengan urutan yang sama. Siklus pertama (High), terjadi pada saat manusia melakukan ekspansi untuk menggantikan generasi yang sebelumnya.

Siklus kedua, dinamakan sebagai siklus kebangkitan (Awakening). Orang-orang pada masa ini lebih spiritual dari siklus sebelumnya, tapi mereka yang hidup di masa ini mempunyai kecenderungan untuk memberontak kepada segala sesuatu yang yang sudah dibuat mapan oleh generasi pertama.

Pada siklus ketiga yang diberi nama sebagai siklus Unraveling, elemen individu dan pengelompokan mempengaruhi masyarakat sehingga timbul berbagai permasalahan yang kemudian memicu kebangkitan generasi keempat.

Pada era masyarakat mengalami berbagai kesulitan sehingga timbul kebutuhan untuk meredefinisi lagi struktur, tujuan dan sasaran yang sudah ditetapkan dalam masyarakat.

Setiap generasi memiliki karakteristik yang berbeda satu sama lain sehingga mereka diberi penamaan yang berbeda. seperti: Prophet, Nomad, Hero, and Artist. Menurut mereka Generasi Y merupakan generasi yang dikategorikan sebagai Hero, dengan karakteristik sangat percaya kepada institusi dan kewenangan, terlihat agak konvensional akan tetapi sangat berpengaruh. Kebanyakan Generasi Y ini dibesarkan pada siklus Unraveling dengan proteksi yang lebih dari generasi sebelumnya, Generasi X.

Ciri-ciri Generasi Y pada setiap tahap kehidupannya akan sangat berbeda. Pada saat muda, Generasi Y ini sangat tergantung pada kerja sama kelompok. Pada saat mereka mulai dewasa mereka akan berubah menjadi orang-orang yang akan lebih bersemangat apabila bekerja secara berkelompok terutama di saat-saat krisis.

Pada saat paruh baya, mereka akan semakin energetik, berani mengambil keputusan dan kebanyakan mereka mampu menjadi pemimpin yang kuat. Pada saat mereka tua, mereka akan menjadi sebagai sekelompok orang tua yang mampu memberikan kotribusi dan kritikan kepada masyarakat.

Pada tahun 2000, berdasarkan suatu penelitian demografis yang sangat luas William Strauss dan Neil Howe menulis buku yang didekasikan kepada Generasi Y dengan diberi judul Millennials Rising: The Next Great Generation.

Di dalam buku ini mereka memakai 1982 dan 2001 sebagai masa di mana Generasi Y mulai dan berakhir. Mereka sangat percaya bahwa semua orang yang lulus SMA sampai tahun 2000 nanti akan sangat berbeda dengan mereka yang lulus SMA sebelum dan sesudah masa itu, karena orang-orang pada masa itu menerima banyak perhatian dari media dan perkembangan politik yang mereka terima. Bahkan William Strauss dan Neil Howe berpendapat bahwa generasi ini akan menjadi generasi yang peduli akan masalah-masalah kemasyarakatan.

Jean Twenge, pengarang buku Generation Me (2007), mempunyai pendapat yang berbeda tentang Generasi Y. Menurutnya, Generasi Y dan bersama-sama Generasi X termasuk generasi yang diberi nama Generation Me.

Ia berpendapat seperti ini, karena dari riset perilaku yang dilakukannya ia melihat bahwa generasi ini meningkat kecenderungan narcissismnya apabila dibandingkan dengan riset yang dilakukan terhadap generasi Baby Boomers, pada saat mereka remaja hingga mereka berumur duapuluhan.

Dengan dasar penelitian ini, ia mempertanyakan pendapat Strauss & Howe tentang generasi ini. University of Michigan’s secara terus menerus sejak tahun 1975 melakukan penelitian terhadap para remaja. Hasil penelitian mereka memperlihatkan:

• Pelajar yang menyatakan kekayaan itu penting semakin meningkat setiap generasi dari 45% pada Generasi Baby Boomers (disurvey pada tahun 1966 dan 1978), menjadi 70% pada Generasi X dan 75% pada Generasi Y atau Millennials.

• Sebaliknya, pelajar yang menyatakan bahwa selalu tahu tentang keadaan politik semakin menurun setiap generasi dari 50% pada Generasi Baby Boomers (disurvey pada tahun 1966 dan 1978), menjadi 39% pada Generasi X dan 35% pada Generasi Y atau Millennials.

• 73% Baby Boomers ingin mengembangkan filosofi yang bermakna, sementara hanya 45% Generasi Y yang mau melakukan hal tersebut.

• 33% Baby Boomers mau terlibat dengan program membersihkan lingkungan dan hanya 33% Generasi Y yang mau melakukan hal tersebut.

Praktek Pengelolaan SDM Bagi Generasi Y

Apabila kita perhatikan data demografi karyawan di perusahaan, kita dapat melihat kalau Generasi Baby Boomers adalah generasi terbesar yang anggotanya sedang aktif bekerja. Penelitian dan observasi memperlihatkan bahwa Generasi Baby Boomers mengidentifikasi atau menggambarkan kekuatan mereka adalah pemikiran-pemikiran tentang organisasi, rasa optimisme dan kemauan untuk bekerja dengan waktu yang panjang (work long hours).

Generasi ini dibesarkan di dalam suatu organisasi dengan struktur organisasi yang hierarkhis daripada struktur manajemen yang datar di mana kerja sama yang timbul di dalam organisasi didasarkan pada tuntutan pekerjaan (teamwork-based job roles).

Sementara Generasi Y, yang mempunyai karateristik yang berbeda dengan Generasi Baby Boomers, juga mempunyai harapan yang sangat berbeda kepada perusahaan yang memperkerjakan mereka. Secara merata Generasi Y mempunyai pendidikan yang lebih baik dari para orang tua, mereka cukup terbiasa dengan teknologi bahkan sebahagian mereka sangat ahli dengan teknologi. Mereka ini mempunyai kepercayaan diri yang tinggi, mampu mengerjakan beberapa tugas dan selalu mempunyai energi yang berlebihan.

Namun di sisi lain Generasi Y ini sangat membutuhkan interaksi sosial, hasil pekerjaan yang dapat dilihat seketika dan keinginan untuk mendapatkan pengembangan yang cepat. Kebutuhan-kebutuhan ini yang sering dianggap sebagai kelemahan dari Generasi Y oleh kolega mereka yang lebih tua terutama mereka yang berasal dari Generasi Baby Boomers.

Berdasarkan pengalaman PPM Manajemen di dalam merekrut Generasi Y, terlihat bahwa Generasi Y itu lebih banyak harapannya kepada perusahaan, sehingga mereka akan pindah pekerjaan lebih banyak daripada generasi-generasi sebelumnya. Untuk menghadapi tantangan ini beberapa perusahaan multinasional sudah melakukan riset sosial dan perilaku yang lebih mendalam untuk Generasi Y.

Institute of Leadership & Management, misalnya, berkolaborasi dengan Ashridge Business School melakukan riset tentang kesenjangan antara Generasi Y yang direkrut dengan para manajernya. Penelitian ini menyimpulkan bahwa Generasi Y sangat menginginkan perusahaan mempunyai sistem yang dapat mengembangkan diri mereka, imbal jasa yang baik dan proses coaching yang jelas. Apabila perusahaan ingin menggunakan Generasy Y sebagai sumber kompetitif mereka maka perusahaan harus menyempurnakan sistem sistem dan proses Human Capital-nya.

Usaha-usaha yang perlu dilakukan oleh perusahaan di dalam proses akuisisi dan mengembangkan Generasi Y, di antaranya adalah:

1. Meredefinisi karakteristik atau ciri ciri karyawan yang diinginkan karena Generasi Y memiliki karakteristik dan ciri yang berbeda. Misalnya, beberapa perusahaan mempunyai kebijakan untuk tidak menerima karyawan yang memiliki tatto, karena tatto dianggap suatu ciri pemberontakan pada suatu institusi.

Sementara populasi Generasi Y yang memiliki tatto ini cukup besar bahkan beberapa diantara mereka memiliki tatto yang lebih dari 1. Bagi Generasi Y sendiri, tatto hanya merupakan suatu bentuk komunikasi tentang indentitas diri mereka, sehingga banyak di antara mereka walaupun memiliki tatto akan tetapi berkomitmen pada profesi yang dipilih. Atau pandangan bahwa tinggal bersama orang tua merupakan pertanda ketidakdewasaan.

Sementara bagi Generasy Y, tinggal bersama orang tua merupakan bentuk relasi sosial yang ingin dipertahankan karena mereka ingin memberi kasih sayang lebih banyak kepada oarang tuanya. Sehingga banyak di antara mereka yang tinggal bersama orang tuanya, namun secara ekonomi mereka yang menanggung kehidupan orang tuanya.

2. Memberikan informasi yang jelas tentang organisasi sejak awal proses rekrutmen sehingga Generasi Y mendapatkan kejelasan kualifikasi apa yang dituntut organisasi dari mereka. Serta hal-hal yang dapat diberikan perusahaan kepada mereka terutama sistem pengembangan karir dan kompetensi, diri mereka, imbal jasa yang baik dan proses coaching yang jelas serta iklim kerja di organisasi.

3. Mempersiapkan lingkungan unit kerja yang akan menerima penempatan Generasi Y untuk pertama kali. Sehingga para atasan Generasi Y di tempat baru memahami perbedaan karakter Generasi Y. Untuk memastikan Generasi Y yang baru masuk dapat beradaptasi dengang baik, Goldman Sachs membuat workshop bagi para atasan Generasi Y, dengan tujuan mereka bisa memahami dan memenuhi kebutuhan Generasi Y akan tanggung jawab yang jelas, umpan balik terhadap kinerja mereka dan memberi kesempatan untuk ikut dalam proses pengambilan keputusan.

4. Generasi Y juga akan membawa perubahan dalam cara penyelesaian pekerjaan karena mereka adalah orang-orang yang sangat suka bekerja dalam kelompok dan memakai teknologi lebih banyak dari generasi sebelumnya.

Apabila di generasi-generasi sebelumnya pembagian pekerjaan itu sifatnya individu, maka pada generasi ini sebaiknya pembagian pekerjaan diberikan per kelompok sehingga mereka mempunyai kebebasan untuk menetapkan tugas masing-masing anggotanya berdasarkan kekuatan mereka.

Perusahaan juga harus bisa memberikan kebebasan kepada mereka untuk menggunakan teknologi dalam bekerja. Apabila mereka menganggap tatap muka bukan merupakan suatu hal yang penting, maka berikan mereka kesempatan untuk berkomunikasi melalui teknologi.

5. Generasi Y selalu ingin mengetahui pandangan manajemen atau umpan-balik dari atasan terhadap pekerjaan yang mereka lakukan. Sayangnya, manajemen kinerja yang berlaku di perusahaan saat ini, biasanya hanya memberi kesempatan 2 kali dalam 1 tahun untuk melakukannya.

Kesempatan ini jelas terlalu sedikit dan terlalu lama untuk Generasi Y. Mereka selalu ingin tahu apabila pekerjaan mereka berhasil dengan baik dan mereka menginginkan adanya umpan-balik saat itu juga. Dari suatu penelitian yang dilakukan terhadap pembaca Majalah Manajemen, diketahui bahwa para karyawan Generasi Y mengharapkan para atasan mereka mampu memberikan tuntutan kerja yang jelas, menumbuhkan budaya kerja yang berorientasi pada kerja sama kelompok, memberikan umpan balik secepat mungkin, memberikan kesempatan penghargaan apabila mereka mampu melakukan suatu tindakan yang beresiko tinggi atau berhasil melakukan suatu inovasi.

Apa yang Harus Dilakukan Perusahaan untuk Mempertahankan Generasi Y?

Membuat suatu strategi untuk mempertahankan karyawan yang berkinerja tinggi dan bertalenta merupakan suatu sasaran penting bagi manajemen puncak di dalam suatu organisasi. Beberapa organisasi telah berhasil membuat suatu strategi untuk mempertahankan karyawan terbaik mereka yang berasal dari Generasi Baby Boomers. Namun untuk mempertahankan karyawan yang datang dari Generasi Y, organisasi tersebut memerlukan suatu pendekatan dan strategi yang sangat berbeda.

Dari paparan di atas, kita dapat melihat perbedaan karakteristik di antara Generasi Baby Boomers dan Generasi Y. Namun isu yang perlu didiskusikan berikutnya adalah seberapa jauh perbedaan antara Generasi Baby Boomers dan Generasi Y. Keterikatan seorang karyawan kepada organisasi sangat dipengaruhi oleh dimensi-dimensi kehidupan yang mempengaruhi kepuasan bekerja karyawan tersebut yang bisa membawa pikiran dan fisik mereka ke tempat kerja.

Guna mengetahui dimensi apa yang mendorong para karyawannya untuk terikat kepada organisasi, suatu organisasi dituntut untuk mencari tahu dimensi-dimensi yang membuat seorang karyawan terikat atau ingin melepaskan diri dari organisasinya (engagement drivers and threats). Untuk menyamakan pemahaman kita semua mengenai engagement drivers and threats, sebaiknya diperjelas dulu pengertiannya.

Engagement drivers adalah dimensi-dimensi yang meningkatkan persepsi seseorang untuk terikat terhadap organisasinya, sementara engagement threats adalah dimensi-dimensi yang menurunkan rasa keterikatan seseorang terhadap organisasinya.

Beberapa engagement drivers and threats yang sering dijadikan dimensi pengukuran dalam penelitian tentang engangement, seperti kesempatan mengembangkan karir, corporate social responsibility, kesejahteraan dan kesehatan karyawan, reputasi organisasi, kesempatan untuk belajar dan dikembangkan, manajemen kinerja, gaya kepemimpinan manajemen madya dan work-life balance.

Dari beberapa riset yang dilakukan oleh berbagai pihak, saya berpendapat bahwa Manajemen Kinerja (managing performance) dan Kesempatan untuk mengembangkan karir (career opportunities) merupakan engagement drivers yang paling penting sementara engagement threats yang sangat besar pengaruhnya adalah nama baik perusahaan (Employer Reputation) dan manajemen kinerja (managing performance).

Engagement di dalam suatu perusahaan biasanya diukur berdasarkan opini seluruh karyawannya dari seluruh unit yang ada di dalam organisasi tanpa memperhitungkan perbedaan generasi. Hal seperti itu, bukanlah praktek yang baik karena organisasi menjadi tidak sensitif terhadap engagement drivers and threats bagi setiap generasi dan bahkan kelompok kerja.

Sebaiknya suatu organisasi juga tidak mengukur engagement berdasarkan dimensi-dimensi yang berhasil membuat organisasi lain mengikat karyawannya. Manajer human capital dan para specialist di dalam suatu organisasi mempunyai kewajiban untuk mencari dimensi engagement di dalam organisasi, sebab dimensi engagement suatu organisasi tidak akan sama dengan organisasi yang menjadi pesaingnya maupun organisasi yang menjadi pemimpin di dalam industri tersebut.

Misalnya, apa yang menjadi engangement drivers dan threats bagi taksi Blue Bird sebagai perusahaan yang memimpin industri taxi tidak akan sama dengan drivers dan threats bagi perusahaan-perusahaan taksi yang menjadi pesaingnya.

Apabila suatu organisasi sudah berhasil mengidentifikasi engagement drivers dan threats yang menjadi ciri khas bagi organisasinya, maka manajemen madya di organisasi tersebut harus segera memutuskan bagaimana menyempurnakan sistem dan proses human capital yang sudah ada.

Misalnya, suatu perusahaan berhasil mengidentifikasi bahwa salah satu engagement drivers-nya adalah perlakukan atasan terhadap bawahannya, maka perusahaan tidak mungkin membuat peraturan yang dapat memuaskan setiap orang dari berbagai generasi.

Hal yang dapat dilakukan oleh perusahaan adalah meredisain tugas setiap atasan dan kemudian memberdayakan mereka agar mampu lebih mengenali sumber motivasi bawahannya dan meningkatkan engagement drivers mereka.

Apa yang Perlu Diperhatikan tentang Generasi Y

Di akhir diskusi ini, saya ingin menyampaikan bahwa perbedaan karakteristik di antara Generasi Y dengan generasi-generasi sebelumnya cukup besar. Generasi Y menuntut beberapa hal dari organisasi yang akan mereka masuki atau organisasi tempat mereka bekerja.

Generasi Y sangat menginginkan perusahaan mempunyai sistem yang dapat mengembangkan diri mereka, imbal jasa yang baik dan proses coaching yang jelas. Namun untuk kesuksesan dalam mengelola Generasi Y, sebaiknya perusahaan mengenali karakteristik Generasi Y yang mereka miliki sehingga manajemen bisa membuat kebijakan human capital yang lebih sesuai dengan mereka.

Walaupun beberapa organisasi telah berhasil membuat suatu strategi untuk mempertahankan karyawan mereka yang berkinerja tingga dan bertalenta. Namun untuk mempertahankan karyawan yang datang dari generasi Y, organisasi tersebut memerlukan suatu pendekatan dan strategi yang sangat berbeda. Organisasi perlu mengetahui engagement driver mana yang lebih mengena bagi organisasi Y sehingga mudah bagi organisasi untuk melakukan penyempurnaan terhadap sistem dan prosedur human capital-nya.


Sumber : Octa Melia Jalal. Head of PPM Center for Human Capital Development.

Microsoft SQL Server & SharePoint License

Few months ago, I have a client that ask me about licensing because one of their product relates to another product that is not come from same brand or company. The database is using SQL Server but the application is not. This post is similar with my case, although SharePoint is still Microsoft family. In this post, I learn about Microsoft licensing call multiplexing. Please read the full article from mirazon below. Happy reading...

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“Do I need SQL CALs when using SharePoint?”  This question came up recently while we were putting together a SharePoint solution for one of our clients … and it wasn’t the first time it has come up.

It’s a natural question. Here’s the scenario: you are setting up a SharePoint server. You need a SQL server on the backend to hold and manipulate all the data that SharePoint will need. But the users and endpoint devices will never touch the SQL server. They will just be accessing the SharePoint server.  So naturally they won’t need SQL CALs, right? Wrong!

Multiplexing

Let me introduce you to the term “multiplexing.”  Multiplexing is essentially where one system sits in front of another system providing services to endpoint devices. Or, as Microsoft puts it in a volume licensing brief devoted to the subject:

‘Multiplexing’ is when customers use hardware or software to pool connections, reroute information, or reduce the number of devices or users that directly access or use a product. Multiplexing can also include reducing the number of devices or users a product directly manages.

This is illustrated in the diagram below. SQL server sits on the backend, the “pooling hardware or software” sits in the middle, and the users and devices access the pooling system from the outside.  SharePoint would be an example of “pooling software.”

But again, the users and endpoints are never touching the SQL server so you would naturally think that SQL CALs would not be needed. However, you would be out of compliance if you did not buy SQL CALs for those users or devices.

Every User or Device Needs a CAL

Here is the key statement by Microsoft on the subject, taken from the same licensing brief:

“Multiplexing does not reduce the number of Microsoft licenses required. Users are required to have the appropriate licenses, regardless of their direct or indirect connection to the product. Any user or device that accesses the server, files, or data or content provided by the server that is made available through an automated process requires a CAL.”

In other words, since SharePoint is accessing the data in the SQL server and the user/endpoint is accessing SharePoint, then the user or endpoint needs a SQL CAL. Essentially, if you access SharePoint then you are accessing SQL as well.

Here is the full diagram from Microsoft’s licensing brief.  It illustrates the point that whether you access the SQL server directly or indirectly, you need a CAL.

The Alternative

By now you may be saying, “If that’s the case, then my SharePoint project just became impossibly expensive! What’s the workaround?”

The other option you have is to use core licenses of SQL instead of server/CAL licenses. There are two ways to purchase SQL 2012:

• You can purchase a server license for the server, and CALs for all your users or endpoint devices; or …
• You can purchase core licenses for all the processor cores within the server. (CALs are not needed for this option.)

If you go with core-based licenses, then all your CAL problems go away.  A million people could access that server and you would be all set … at least from a licensing standpoint.  (But from a performance standpoint, I wouldn’t recommend a million hits on your server all at once.)

Which Option Should I Choose?

Last question on this topic: “At what point is it more cost effective for me to go with core-based licenses instead of server/CAL licenses?” The answer to that question depends on a number of factors (number of CPU cores running SQL, number of users, and number of devices), so let’s set up a simple example:

Let’s say you are a small shop and you want to have SQL Standard running on a single server with a dual-core processor. Should you go with core licenses or server/CAL licenses?

Well, it depends on the number of users or devices that need to access SQL. In this situation it would cost the same for you to buy core licenses as it would for you to buy a server license and 30 CALs.

Server/CAL Licensing vs. Core-Base Licensing for SQL Standard:

• 1 Server + 30 CALs = $7,168
• 4 Core Minimum = $7,172

So if you have over 30 users, then you should go with core licenses. If you have less than 30 users, then server/CAL licenses would be the way to go. (Note that there is a four-core minimum purchase if you go with the core licenses. Even though you only have a dual-core processor, you still need to license four cores.)


Original Source : Mirazon

Capex Vs Opex Definition & IT Point Of View

In this fast growing world, we are facing reality that most of companies today very selective of put their capital on something new, especially for something that is not their core business. This is my point of view from "IT Consultant". They (companies) are prefer opex to capex for their IT investment, whether it is software or hardware. This is why many ISV in Indonesia are compete to grow their data center and offer "Cloud" to their clients. The clients will improve their efficiency and reduce man power, but still could running their main business and remain improve their customer satisfaction. By the way... What is capex and opex? Below, you will find the article from diffen is very useful. Happy reading.

Capex vs. Opex

Capex (or Capital Expenditure) is a business expense incurred to create future benefit i.e. acquisition of assets that will have a useful life beyond the tax year. e.g. expenditure on assets like building, machinery, equipment or upgrading existing facilities so thier value as an asset increases.

On the other hand, those expenditures required for the day-to-day functioning of the business, like wages, utilities, maintenance and repairs fall under the category of Opex (operational expenditure). Opex is the money the business spends in order to turn inventory into throughput. Operating expenses also include depreciation of plants and machinery which are used in the production process. 

Examples
Capital expenditures include acquiring fixed assets (tangible, e.g. machinery or intangible e.g. patents), fixing problems with an asset, preparing an asset to be used in business, restoring property so that value is added, or adapting it to a new or different use.

Operating expenditures include license fees, maintenance and repairs, advertising, office expenses, supplies, attorney fees and legal fees, utilities such as telephone, insurance, property management, property taxes, travel and vehicle expenses, leasing commissions, salary and wages, raw materials.

Accounting for Capex and Opex
The crux of the matter lies in the way these expenditures are accounted for in an income statement.

Since capital expenses acquire assets that have a useful life beyond the tax year, these expenses cannot be fully deducted in the year in which they are incurred. Instead, they are capitalized and either amortized or depreciated over the life of the asset. Intangible assets like intellectual property (e.g. patents) are amortized and tangible assets like equipment are depreciated over their lifespan.

Operating expenditure, on the other hand, can be fully deducted. "Deducted" means subtracted from the revenue when calculating the profit/loss of the business. Most companies are taxed on the profit that they make; so what expenses you deduct impacts your tax bill.

What is preferred: Capex or Opex?
From an income tax perspectives, businesses typically prefer OpEx to CapEx. For example, rather than buy laptops and computers outright for $800 apiece, a business may prefer to lease it from a vendor for $300 apiece for 3 years. This is because buying equipment is a capital expense. So even though the company pays $800 upfront for the equipment, it can only deduct about $250 as an expense in that year.

On the other hand, the entire amount of $300 paid to the vendor for leasing is operating expense because it was incurred as part of the day-to-day business operations. The company can, therefore, rightfully deduct the cash it spent that year.

The advantage of being able to deduct expenses is that it reduces income tax, which is levied on net income. Another advantage is the time value of money i.e. if your cost of capital is 5% then saving $100 in taxes this year is better than saving $104 in taxes next year.

However, tax may not be the only consideration. If a public company wants to boost its earnings and book value, it may opt to make a capital expense and only deduct a small portion of it as an expense. This will result in a higher value of assets on its balance sheet as well as a higher net income that it can report to investors.

Capex and Cash Flow
Investors often look not only at the revenue and net income of a company, but also at the cash flow. The reported profit, or net income, can be "manipulated" via accounting techniques and hence the idiom "Income is opinion but cash is fact." Operating expenses directly reduce the Operating Cash Flow (OCF) of the company. Capex does not figure in the calculation of OCF but capital expenditures reduce the Free Cash Flow (FCF) of the company. Some investors treat FCF as a "litmus test" and do not invest in companies that are losing money, i.e. have a negative FCF.

Amazon is an example of a company with very high capital expenses. The following chart, by Benedict Evans, shows the growth in OCF, capex and FCF for Amazon since 2003.

Source : Diffen