Big Data Technologies – Most Mandatory Proficiencies to Grab a Career

Anyone running out of job ? Seriously?… No more worries about employment when you have Big Data around.  Presenting to my readers the tips and mandatory skills to glow with bright Data jobs in your hands in this Data world.

Today the Big data technologies are one of the newest technologies in the market and it will be a clever idea to grab the jobs of these trending technologies before it is too late. We should groom up with all the skills and land into these high demanding job profiles of big data technologies at its newest phase before these jobs become too common in the market. So get all the knowledge possible with big data technologies and hurry up to get hired.

Mathematical Analysis

111Big data is all about calculations. Always people with an educational background in mathematics and analytics are preferred to be working in data analytics. So seeing into the career scope of present age it is advisable for our new generations to strengthen their mathematics and real-time practices by undergoing degrees in mathematics, engineering and statistics.



The last two years in the industry has proved the demand and it is clear that for the present and coming years Hadoop is going to rule the industry. Seeing the speed how the software vendors are initiating Hadoop in their enterprises, it is clear that Hadoop’s existence in the market will be a long story. Since the field of big data is really the strongest, so using Hadoop is immensely important in the technologies dealing with huge sets of unstructured data. Dealing big data with Hadoop requires great expert technicians of Hadoop. It’s an opportunity to fit into the demand of the industry by learning core skills of Hadoop like HDFS, MapReduce, Oozie, Hive, Flume, Pig, Hbase, and YARN.

Programming Languages


Coders have got no expiry dates. This is because, whichever technologies you go, you will always be in need of programmers. Because programming gives life to software embedded inside hardware. In this big data industry, if you have an experience in programming of different languages like C,C++, Java, Python, etc then  your demand will never really going to die.



Like Hadoop Spark has got the strength of fast performance, making it possible for applications to run 100 times faster.  The increasing of the in-memory stack can be an alternative to the processor analytics of Hadoop. In these big data world, Spark needs a huge number of manpower who is proficient with the core components of it.

Machine Learning


In this big data world, artificial intelligence is getting a forward push to develop and raise newer and exciting humanoids. With the enhancement of artificial technology, more scientists and engineers are in a high requirement in order to meet the workforce. Hence, machine learning is a must required skill in order to get a job in artificial intelligence in this big data era.



Today the NoSQL databases are working on the operating sides of the big data industry. NoSQL databases are used with high priority in the websites and mobiles along with the Hadoop commands. Same like Hadoop, this technology also stands in the similar level of demand in the tech planet.







nmIn this competitive era of big data technology, learning SQL holds a lot of demand. Although NoSQL is under the spotlight, but still, SQL is on a stable demand in the market and still is gaining a lot of funding and implementation in the industry today. So seeing the firm demand  of SQL it is on priority to brush up your SQL skills sooner.

Tableau or QlikView


Working with data needs the ability to visualize, discovering the shape, size, structure and arrangement of data. Data visualization is a must for you to become a data artist and make all kinds of creativity you will assure on data. Experts in tableau and Qlikview with the ability for data visualization mainly focusing on to business intelligence and software visualizations are on priority requirement in the tech house today.

Resourcefulness wins Forever


Technologies come, technologies evolve and technologies go. New jobs will get introduced and after a certain age, its demand reduces. But creativity never dies. If you develop your creative skills, then no matter which technology runs in the market, you will always manage to find a way to get into it and you will never ever go unemployed.

How big data is changing the database landscape for good

Mention the word “database,” and most people think of the venerable RDBMS that has dominated the landscape for more than 30 years. That, however, may soon change.
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A whole crop of new contenders are now vying for a piece of this key enterprise market, and while their approaches are diverse, most share one thing in common: a razor-sharp focus on big data.

Much of what’s driving this new proliferation of alternatives is what’s commonly referred to as the “three V’s” underlying big data: volume, velocity and variety.
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Essentially, data today is coming at us faster and in greater volumes than ever before; it’s also more diverse. It’s a new data world, in other words, and traditional relational database management systems weren’t really designed for it.

“Basically, they cannot scale to big, or fast, or diverse data,” said Gregory Piatetsky-Shapiro, president of KDnuggets, an analytics and data-science consultancy.

That’s what Harte Hanks recently found. Up until 2013 or so, the marketing services agency was using a combination of different databases including Microsoft SQL Server and Oracle Real Application Clusters (RAC).

“We were noticing that with the growth of data over time, our systems couldn’t process the information fast enough,” said Sean Iannuzzi, the company’s head of technology and development. “If you keep buying servers, you can only keep going so far. We wanted to make sure we had a platform that could scale outward.”

Minimizing disruption was a key goal, Iannuzzi said, so “we couldn’t just switch to Hadoop.”

Instead, it chose Splice Machine, which essentially puts a full SQL database on top of the popular Hadoop big-data platform and allows existing applications to connect with it, he said.

Harte Hanks is now in the early stages of implementation, but it’s already seeing benefits, Iannuzzi said, including improved fault tolerance, high availability, redundancy, stability and “performance gains overall.”

There’s a sort of perfect storm propelling the emergence of new database technologies, said Carl Olofson, a research vice president with IDC.

First, “the equipment we’re using is much more capable of handling large data collections quickly and flexibly than in the past,” Olofson noted.

In the old days, such collections “pretty much had to be put on spinning disk” and the data had to be structured in a particular way, he explained.

Now there’s 64-bit addressability, making it possible to set up larger memory spaces, as well as much faster networks and the ability to string multiple computers together to act as single, large databases.

“Those things have opened up possibilities that weren’t available before,” Olofson said.

Workloads, meanwhile, have also changed. Whereas 10 years ago websites were largely static, for example, today we have live Web service environments and interactive shopping experiences. That, in turn, demands new levels of scalability, he said.

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Companies are using data in new ways as well. Whereas traditionally most of our focus was on processing transactions — recording how much we sold, for instance, and storing that data in place where it could be analyzed — today we’re doing more.

Application state management is one example.

Say you’re playing an online game. The technology must record each session you have with the system and connect them together to present a continuous experience, even if you switch devices or the various moves you make are processed by different servers, Olofson explained.

That data must be made persistent so that companies can analyze questions such as “why no one ever crosses the crystal room,” for example. In an online shopping context, a counterpart might be why more people aren’t buying a particular brand of shoe after they click on the color choices.

“Before, we weren’t trying to solve those problems, or — if we were — we were trying to squeeze them into a box that didn’t quite fit,” Olofson said.

Hadoop is a heavyweight among today’s new contenders. Though it’s not a database per se, it’s grown to fill a key role for companies tackling big data. Essentially, Hadoop is a data-centric platform for running highly parallelized applications, and it’s very scalable.

By allowing companies to scale “out” in distributed fashion rather than scaling “up” via additional expensive servers, “it makes it possible to very cheaply put together a large data collection and then see what you’ve got,” Olofson said.

Among other new RDBMS alternatives are the NoSQL family of offerings, including MongoDB — currently the fourth most popular database management system, according to DB-Engines — and MarkLogic.
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“Relational has been a great technology for 30 years, but it was built in a different era with different technological constraints and different market needs,” said Joe Pasqua, MarkLogic’s executive vice president for products.

Big data is not homogeneous, he said, yet in many traditional technologies, that’s still a fundamental requirement.

“Imagine the only program you had on your laptop was Excel,” Pasqua said. “Imagine you want to keep track of network of friends — or you’re writing a contract. Those don’t fit into rows and columns.”

Combining data sets can be particularly tricky.

“Relational says that before you bring all these data sets together, you have to decide how you’re going to line up all the columns,” he added. “We can take in any format or structure and start using it immediately.”

NoSQL databases don’t use a relational data model, and they typically have no SQL interface. Whereas many NoSQL stores compromise consistency in favor of speed and other factors, MarkLogic pitches its own offering as a more consistency-minded option tailored for enterprises.

There’s considerable growth in store for the NoSQL market, according to Market Research Media, but not everyone thinks it’s the right approach — at least, not in all cases.

NoSQL systems “solved many problems with their scale-out architecture, but they threw out SQL,” said Monte Zweben, Splice Machine’s CEO. That, in turn, poses a problem for existing code.

Splice Machine is an example of a different class of alternatives known as NewSQL — another category expecting strong growth in the years ahead.

“Our philosophy is to keep the SQL but add the scale-out architecture,” Zweben said. “It’s time for something new, but we’re trying to make it so people don’t have to rewrite their stuff.”

Deep Information Sciences has also chosen to stick with SQL, but it takes yet another approach.

The company’s DeepSQL database uses the same application programming interface (API) and relational model as MySQL, meaning that no application changes are required in order to use it. But it addresses data in a different way, using machine learning.

DeepSQL can automatically adapt for physical, virtual or cloud hosts using any workload combination, the company says, thereby eliminating the need for manual database optimization.

Among the results are greatly increased performance as well as the ability to scale “into the hundreds of billions of rows,” said Chad Jones, the company’s chief strategy officer.

An altogether different approach comes from Algebraix Data, which says it has developed the first truly mathematical foundation for data.

Whereas computer hardware is modeled mathematically before it’s built, that’s not the case with software, said Algebraix CEO Charles Silver.

“Software, and especially data, has never been built on a mathematical foundation,” he said. “Software has largely been a matter of linguistics.”

Following five years of R&D, Algebraix has created what it calls an “algebra of data” that taps mathematical set theory for “a universal language of data,” Silver said.

“The dirty little secret of big data is that data still sits in little silos that don’t mesh with other data,” Silver explained. “We’ve proven it can all be represented mathematically, so it all integrates.”

Equipped with a platform built on that foundation, Algebraix now offers companies business analytics as a service. Improved performance, capacity and speed are all among the benefits Algebraix promises.

Time will tell which new contenders succeed and which do not, but in the meantime, longtime leaders such as Oracle aren’t exactly standing still.

“Software is a very fashion-conscious industry,” said Andrew Mendelsohn, executive vice president for Oracle Database Server Technologies. “Things often go from popular to unpopular and back to popular again.”

Many of today’s startups are “bringing back the same old stuff with a little polish or spin on it,” he said. “It’s a new generation of kids coming out of school and reinventing things.”

SQL is “the only language that lets business analysts ask questions and get answers — they don’t have to be programmers,” Mendelsohn said. “The big market will always be relational.”

As for new types of data, relational database products evolved to support unstructured data back in the 1990s, he said. In 2013, Oracle’s namesake database added support for JSON (JavaScript Object Notation) in version 12c.

Rather than a need for a different kind of database, it’s more a shift in business model that’s driving change in the industry, Mendelsohn said.

“The cloud is where everybody is going, and it’s going to disrupt these little guys,” he said. “The big guys are all on the cloud already, so where is there room for these little guys?

“Are they going to go on Amazon’s cloud and compete with Amazon?” he added. “That’s going to be hard.”

Oracle has “the broadest spectrum of cloud services,” Mendelsohn said. “We’re feeling good about where we’re positioned today.”

Rick Greenwald, a research director with Gartner, is inclined to take a similar view.

“The newer alternatives are not as fully functional and robust as traditional RDBMSes,” Greenwald said. “Some use cases can be addressed with the new contenders, but not all, and not with one technology.”

Looking ahead, Greenwald expects traditional RDBMS vendors to feel increasing price pressure, and to add new functionality to their products. “Some will freely bring new contenders into their overall ecosystem of data management,” he said.

As for the new guys, a few will survive, he predicted, but “many will either be acquired or run out of funding.”

Today’s new technologies don’t represent the end of traditional RDBMSes, “which are rapidly evolving themselves,” agreed IDC’s Olofson. “The RDBMS is needed for well-defined data — there’s always going to be a role for that.”

But there will also be a role for some of the newer contenders, he said, particularly as the Internet of Things and emerging technologies such as Non-Volatile Dual In-line Memory Module (NVDIMM) take hold.

There will be numerous problems requiring numerous solutions, Olofson added. “There’s plenty of interesting stuff to go around.”

Backblaze lights up cloud storage with dirt-cheap prices

money-saving-cloud-future-100613728-primary.idgeBackblaze slashes prices on cloud storage to a half-cent per gigabyte per month, but the lack of Amazon API compatibility might limit its appeal

Backblaze, the backup service company that garnered attention for publishing its internal statistics about hard drive failure rates, is throwing open the doors on a cloud storage service with rock-bottom prices.

According to a blog post announcing the new service and its pricing page, Backblaze’s B2 Cloud Storage costs for 0.05 cents per gigabyte per month. Uploads are free; downloads are 5 cents per gigabyte (plus a fee of 0.4 cents per 1,000 transactions). A free tier is also available, where up to 10GB can be stored at no cost, albeit with a download limit of 1GB or 2,500 downloads per day, whichever comes first.

Backblaze sees its main customers as developers, who can access B2 through a RESTful API, and users, who can go through a Web-based interface to upload data. The latter will probably see B2 as a Dropbox competitor, although B2 doesn’t currently have desktop or mobile clients like Dropbox.

Developers and enterprise IT customers could use B2 as a cheap mirror for data either in an existing cloud storage service or on-premises data center. In that case, B2’s value doesn’t revolve around its price, but whether the bandwidth and latency to and from the B2 data center will be up to snuff.

Another possible issue: B2 is served by only one data center. According to a discussion thread on Hacker News (with replies by self-identified Backblaze employee brianwski), there are plans to add another data center due to the existing one running out of space. Also under discussion is the possibility of an S3-compatible API — the current one doesn’t have it — but it would require the use of load-balancing technology that Backblaze originally eschewed in order to keep costs down.