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Dealing with Big Data and Analytics

Current trends and most adopted tools

Jueves, 9 Agosto, 2018

big data

Big Data Analytics technologies are considered key players in today’s Digital Transformation processes. From its main trends to its most important tools and environments, they perform a disruptive role in businesses development towards present and future challenges.

Big Data has become one of the great buzzwords in this day and age. However, the term has been in use by experts for almost three decades. The New York Times published a story about the etymology of Big Data, and the man behind the invention of the term it was John Mashey, chief scientist at Silicon Graphics in the 90s.

Big and small enterprises, concerned about the Digital Transformation of their companies, are adopting Big Data tech to acquire sophisticated decision-making processes driven by data.

Digital Transformation is a broad concern among company executives, since technology affects businesses on almost every level. According to Daniel Newman, analyst at Forbes, Digital Transformation is “an imperative in today’s business market” (…) “and companies unable or unprepared for those changes will quickly fall to the bottom of the pack”.

But what is Big Data and Analytics? As TechRadar says, roughly speaking there are three Vs involved: volume, variety and velocity. Those are the characteristics of the extremely large quantities of data collected that can be analysed afterwards to gain valuable business insights.

The adoption and applications of Big Data are so vast, it couldn’t be explained in just one article. Our main goal here is to deliver a glimpse of its most popular technologies and most used open-source environments and tools.

 

Big Data’s latest trends and most important applications today

The possibilities that Big Data and Analytics can bring (and have already brought) to numerous markets are immeasurable. From real-time data gathered through sensors in supermarket shopping carts to patient data collection in a self-monitoring Telemedicine approach to future healthcare; options seems limitless when it comes to these kind of technologies.

Another tech intimately related to Big Data is IoT (Internet of Things). Everyday electronic devices turned into receptors, connected to the Internet and sharing real-time data collectors. According to SmartDataCollective, IoT spending will reach $6 trillion by 2021, creating a responsive smart network that will be useful for big data solutions to exploit. Retail, security and healthcare are among the top sectors that will benefit from devices used for data collection.

Big Data has provided business intelligence from the gathering of huge amounts of data. The next step towards analysis is adopting a Predictive Analytics framework. Although Dataversity underlines that this type of technology is still in its infancy, could be one of the most important trends in 2018 regarding Big Data. Forbes’ contributor Kimberly A. Whitler mentions it is the transformation of Analytics into action: “While descriptive analysis investigates what has happened in the past (…), predictive analytics uses existing data and trends to predict what might happen in the future”.

 

Open-source environments that are a must for Big Data professionals

Although giant tech corporations like Microsoft offer their Big Data packages and environments, when it comes to talent recruitment, almost every company desires professionals skilled in some of the most adopted open-source tools.

According to OpenSourceForU.com, the main products by the Apache Software Foundation, Hadoop and Spark, are a key to success in order to find a job in today’s highly demanding IT industry. Hadoop has been around for over a decade but its demand has not yet shown any signs of exhaustion. In its own website, Apache Hadoop is defined as a “framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models”. Scalability and distributed computing are two of its main strengths.

As BigDataMadeSimple states, Hadoop’s free version is not easy to use, but many companies offer friendlier version of this open-source system. Shining out from this set of variations is the one provided by Cloudera, which is also one of the most used and adopted services.

Regarding Apache Spark, it is a unified analytics engine for large-scale data processing that especially shines when proving its velocity. The company says it can run workloads 100 times faster than any other product on the market.

Another scalable tool capable of delivering a high performance, within the Apache range, is Cassandra. NewGenApps highlights its capacity to manage massive amounts of data across many commodity servers. This can also happen in a cloud infrastructure and its decentralized nature leaves no single point of failure.

Beyond the wide array of Apache tools and environments, there are many providers in the Big Data and Analytics sector. MongoDB sparkles with a client portfolio of prestigious names like Expedia, Forbes, Bosch and MetLife. Derived from the word humongous, its products are programmed in C++, have document-oriented storage and are meant and built to store and tackle humongous amounts of data.

Among the other systems recommended to achieve a job in the Big Data industry is Elastic Search. DigitalVidya says about it that “allows you to extract data from any source and use it for analytics and visualization”. It also an open-source set of tools capable of performing and combining many type of searches in any way the client wants to tackle them.


 

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