Why Hadoop is perfect for managing BIG data

Anyone that’s spent any amount of time researching or reading about BIG data will have come across the term “Hadoop” at some point. In simple terms, Hadoop is a project with aims of developing open-source software for use in analysis, processing and distribution for BIG data.

How does Hadoop work, exactly?  If you can imagine software being used, in an application layer, to scale up or down as necessary (this could include multiple servers and untold numbers of individual machines), then you’re getting the right idea. The project itself is chiefly composed of 4 separate modules, each with its own specific area of functionality:

From the Apache Hadoop site:

• Hadoop Common -The common utilities that support the other Hadoop modules.

• Hadoop Distributed File System – A distributed file system that provides high-throughput access to application data.

• Hadoop YARN – A framework for job scheduling and cluster resource management.

• Hadoop MapReduce – A YARN-based system for parallel processing of large data sets.

Believe it or not, the technology which is driving Hadoop isn’t necessarily completely original; in fact, the Hadoop project is descended from a project called “Nutch”. But the story doesn’t end there, the Nutch project is actually a slight refinement of technologies which Google created for use in large-scale indexing of content. Hadoop has some special abilities when it comes to handling large data sets; for example, it’s very good at processing both structured and unstructured data. In other words, we’re talking about deep analysis and organization here which wouldn’t normally be possible with different degrees of structured data.

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Basically, you can run Hadoop on hundreds of servers which share no resources (memory) and it will magically organize your data. If you have a number of servers running with the software installed, it will redistribute your bulk data across all these servers in an effort to organize it. Hadoop is also very safe in terms of potential data loss scenarios; like in most cloud computing setups, data is copied across to multiple servers allowing for increased security and quick recovery in the event of loss or catastrophic failure.

At this point you’re probably wondering where Hadoop might be used, right? The real question is, are there any large scale data processing projects that you can’t use Hadoop for? Online retailers can benefit from using Hadoop; it might allow them to present specifically targeted search queries and ads to the right customers at the right times. Likewise, it would even be possible to use Hadoop to break down and analyze a large amount of customer purchase records (in an effort to boost sales), perhaps highlighting some area that is being neglected. But Hadoop can also be used to help break down data and identify patterns in other areas as well; finance is an oft referenced example in this regard.

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In many ways, Hadoop is a software solution / approach to BIG data management that functions in a very similar manner as cloud computing. How’s that? Well, given that both Hadoop and the cloud are essentially elastic, scalable technologies which are driven largely by software, and have the ability to control and requisition computing power from multiple machines…isn’t it fairly obvious? Because these two technologies exhibit close similarities and are compatible, it’s well within reason to assume that they will likely merge to some extent. After all, the proliferation of exceedingly large amounts of data continues unabated, cloud computing is “on deck” to replace grid computing, and people are going to need solutions for crunching / organizing BIG data. Then of course there’s the realization that (in many ways) cloud computing is simply another way of approaching or taking advantage of certain forms of BIG data. Many big businesses are already installing Hadoop into their own IaaS; surely this is a sign of bigger things to come.

In short, while there are different ways of managing BIG data, Hadoop presents one of the most affordable, customizable and available solutions attainable. Additionally, because its open-source, we’re likely to see notable improvements and upgrades arriving for quite a long time at little to no extra cost(s).

What is BIG data and what are its challenges?

In our electronically connected society, nearly everything we do creates some type of data. Aside from the obvious things like information stored or added via computers and the internet, there is sales tracking, GPS, as well as other forms of data. At the same time, the level of data which we (as a global society) are adding on a daily / annual basis is increasing exponentially.

What is BIG data? From a simple standpoint, BIG data is any pool of information which has grown to such a size as to make management, organization or extrapolation (of said collection) difficult. Likewise, BIG data doesn’t always come in an easily quantifiable form either. You might have some BIG data pools which exhibit some form of structure (sales records would be a great example of this), while others are completely unstructured (for instance, most of the information being shared or stored via social media sites).

In terms of challenges, BIG data faces quite a few, like:

• Extracting detail-oriented conclusions from BIG data sets very quickly

• Creating analysis methods for different types of large data sets

• Making BIG data faster and easier to access

• How to create structured data from unstructured sources

• Accessing enough computational power to process extremely large amounts of data in a timely manner

• Developing better systems for securing BIG data

• How to deliver particular data (from larger data sets) to specific users in real time

• Figuring out efficient methods and means of storing BIG data (for short and long-term applications)

Any way you want to look at it, each one of these challenges (including many others) must be met with suitable solutions in the very near future. This isn’t an optional area in which businesses and individuals can decide whether or not they want to utilize, BIG data is everywhere now; it has worked its way into the very fabric of our society. Luckily, there are plenty of potential solutions and technologies which are being implemented on all fronts which are more than capable of helping to tame BIG data.

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One of the most obvious pairings for BIG data is none other than cloud computing. The cloud’s ability to requisition nearly unlimited resources is exactly what is needed when it comes to analyzing and processing extremely large pools of data. As many of you might already be aware, even the most powerful and sophisticated super computers don’t possess the sheer horse-power that an extended cloud network solution can access.

But analysis isn’t the only thing the cloud is good for (where BIG data is concerned); storage, organization and access are all much easier to deal with too. Additionally, many companies are using cloud computing to actually design BIG data solutions for unique problems. Furthermore, once applications or components have been created and deployed, they can be more easily copied and modified via cloud computing, making it easier to devise more customized BIG data solutions.  

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If there’s one thing that you should remember about BIG data, it’s that it isn’t going anywhere. In other words, you’re only going to be hearing more and more about BIG data as time rolls forward. Why, you ask? Because (as previously stated) the proliferation of data continues to accelerate, and it all has to go somewhere, right?

The emergence of BIG data as a conventional area of employment (in and of itself) actually presents some very unique opportunities for IT professionals who realize what’s going on. Many experts are forecasting that careers for those with a concentration in BIG data may well be among the most highly sought-after IT workers in the very near future. This is why those IT careerists who are serious about meeting the demands and shifts which are coming should complete some form of BIG data certification program.

The (US) Federal Government is capitalizing on BIG data technology

It could be argued that large governments are the perfect candidates for BIG data technology. First off, they routinely process a great deal of information already, and this extends into many different areas as well. Yes, if ever there was a group that could really use BIG data tools to create order it would have to be the US federal government. Well, there’s no need to wait for it, because this is exactly what’s been going on recently; the federal govt. has been pushing for increased use of BIG data management with aims of also instituting similar practices at the stage and local levels.

To make a long story short, the government is plugging into a concept that many in the upper end of the technological community have been kicking around for quite a while; it’s the notion that data itself is fast becoming viewed and used as another potential source of revenue. Specifically, that data itself has some intrinsic value which not only makes it worth collecting on its own merit, but that it can also provide valuable insights when taken as a large collective whole. In other words, if you look closely at any large collection of data, you’ll begin to notice that certain sectors of said data (once organized) tend to relate to others in distinctively different ways.

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In the same way that some algorithms are closely held as valuable property, to be used in the US stock exchange (high frequency trading) and for facilitating internet searches (Google’s algorithm), BIG data can allow individuals and organizations to extract their own. It is the relationships existing in networks of seemingly unrelated data pools which seem to be the most valuable. Sure, any large amount of collected data will have a number of potential uses, but it is the larger inferences which are uncovered that are really precious. That’s essentially how many algorithms or formulas are discovered, they are reflections of some larger types of relationships which exist on multiple levels and stem from one source of connected materials.

Anyway, getting back on point; the Federal government in the US has clearly seen the light as far as BIG data is concerned. As part of the Obama administration’s attempt at improving efficiency of operations and utilization of technology; industry experts, government leaders, and academics have come together to address the challenges of BIG data and how it might best be used in government. Also, this comes at a time when virtually all sectors of every governmental body in the world are facing slowing growth and economic unrest. Basically, BIG data is yet another way of creating additional value through a steady medium, which is very much welcome at this point.

In 2011, around $200 million was put forth toward the development of BIG data research projects. The goal was (and still is) to look for solutions in some of the more pressing areas like health care, criminal fraud, emergency preparedness and of course, police operations. Each of these areas of government routinely deal with very large databases of information and generally aren’t used in any particularly strategic manner; hopefully with the introduction of BIG data analysis however, this will change.

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How might such large pools of data be used to address issues? In health care for example, gathered statistics can help to determine future averages in terms of those afflicted with certain types of ailments. In turn, this data can be used to determine the future costs in individual areas of the health care establishment, which would allow for much more accurate budgeting and prevent such things as unexpected shortfalls. Likewise, in cases where certain governmental agencies are searching for malicious hackers and cyber criminals, continual scrutiny of large amounts of data might allow for both deterrence as well as forensic analysis. Imagine being able to process a very large amount of data and almost instantly being able to see where cyber criminals have been and what they’ve been up to over time.

Perhaps even more important (in light of the staggering number of natural disasters we’ve seen emerge in the last several years) is the government’s use of BIG data management for all emergency preparedness programs. For an organization like FEMA, it’s not a question of “is something going to happen?” as much as “when will it happen?” By having a coterie of BIG data tools on hand to assist with all emergency operations, more lives can hopefully be saved, more property protected, and rebuilding operations instituted in a timelier manner.

Currently, the Federal government is focusing on BIG data training, education and certification. The big hope is that in the coming years there will be a large enough influx of individuals steeped in IT practices and BIG data management to meet the growing demand of the government.

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