The year 2016 was a remarkable year for big data as more and more organizations stored, processed and extracted value from data of all forms and all sizes. Systems that support large volumes of both structured and unstructured data will observe a rise in the year 2017. The market will be demanding platforms which could help data custodians govern and secure big data. This will empower end users to analyze data.
The year 2017, as we anticipate, will be facing some challenges for analytics practitioners to deal with. As a reaction to these challenges, the year foresees the arrival of new technologies and new methods of working in order to mitigate these challenges.
Let’s view the outlined big data analytics trends for the forthcoming year 2017.
1. Big Data Expansion
With the proliferation of big data, it becomes imperative to keenly and quickly analyze data in order to gain valuable insight. Enterprises must now be aiming to turn their unused terabytes of big data which is classified into dark data into useable data. Big Data still has not yielded substantial results which organizations require for developing insights and innovative offerings to get an edge over competitors.
2. Wider Adoption of Hadoop
Today more and more organizations are adopting Hadoop ecosystem. Hadoop when placed successfully are able to crunch a large amount of data using advanced analytics to find chunks of valuable information in order to make profitable decisions. The year 2017 will observe customers demanding for analytics on all data. Platforms which are data and source agnostic will prosper while the ones which are purpose-built for Hadoop and fail to deploy across a variety of use cases will drop out.
3. Exponential Growth of Embedded Analytics
Various studies and multiple surveys pointed out the fact that 65% organizations are now using Embedded Analytics in their organizations while almost 30% are considering the same. Embedded analytics comprises of any consumer-facing BI and analytics tools which are integrated into software applications, therefore, operating as a component of the native application itself rather than a separate platform. As the standards of governance are improved and end users are able to utilize higher quality data therefore embedded analytics are of great help. Embedded analytics also help in pointing out insights quickly as there is no time wasted in requesting reports from external agents.
4. The Three Vs Driving Big Data Investments
Gartner defines big data as the three Vs: high-volume, high-velocity, high-variety of information. Therefore, another big data trend this year are these three V’s. Variety is becoming the single biggest driver of big data investments. In 2017, this trend will continue to grow as enterprises are seeking to integrate more sources and focus on big data. Schema-free JSON, nested types in other databases (relational and NoSQL), and many data formats are multiplying and connectors are becoming very important. With the year 2017, analytics platforms will be evaluated on the ability to offer direct connectivity of these different sources.
5. Mixed Bag of IoT, Big Data, Cloud and Cybersecurity
The year 2017 will be a conglomeration of data management technologies which are data preparation, data analytics, data integration, data quality and much more. With more and more dependency on smartphones and other smart devices inter-connectivity and machine learning will become quite important and it necessitates the need of protecting these assets from cyber security threats. IoT is generating massive volumes of structured and unstructured data and there is continuous data being deployed on cloud services. With speedy innovation in storage and managed services of capturing process, accessing and understanding data poses a significant challenge. This results in demand for growing of analytical tools which seamlessly connect and combine a wide variety of cloud-hosted data sources. These analytical tools help businesses in exploring and visualizing any data stored anywhere.
Big Welcome To Trendy 2017big data and cloud will not only help organizations to deal with huge amount of data but will also help organizations to address business challenges. This space is still evolving and organizations need to react and adapt quickly to monetize true potential of their data!
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References: information-management.com, kdnuggets.com, dzone.com, tableau.com, channels.theinnovationenterprise.com, ibmbigdatahub.com