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Top 10 Insights about Big Data Platforms

Data! Data is deemed to be the most important and valuable asset for any organization operating in the modern business world. We all accept the fact that data is large, and it is apparently infinite. Moreover, it is complex, at times structured, and sometimes unstructured. Today, in the modern world that we live in, data processing, storage, and analysis is not a simple task, and certainly not with the traditional tools at disposal. Hence, the invention of Big Data! Let us gain an insight into the latest Big Data trends.

Top 10 Insights about Big Data Platforms

Through this blog, we will not only attempt and explore the latest trends associated with Big Data, but also some technologies augmenting its functionalities.

Latest Big Data Platforms

  • IBM Big Data Platform

IBM is considered to be a comprehensive big data platform addressing all the big data challenges encountered by businesses. The core competencies of IBM Big Data Platform are information integration & governance, a Hadoop-based analytics; data-warehousing, and stream computing. It is an incorporation of traditional technologies and modern day technologies. The traditional technologies facilitate structured and repeated tasks. On the other hand, the new technologies facilitate flexibility and speed and are perfect for exploration of unstructured data analysis and ad-hoc data exploration.

  • SAP HANA

SAP HANA is looked at as a smart choice, since it focuses on running the analytics applications in a smarter manner, thus expediting business processes and helping to create simpler data infrastructures. HANA is formulated for next-generation analytics and applications. SAP HANA acts as the foundation for all the data requirements by enabling integration of all sorts of data, and through the application of advanced analytical processing to seek detailed information.

  • Pivotal Big Data Suite

Pivotal Big Data Suite is considered to be an extremely useful database technology, as it helps organizations accelerate the process of digital transformation. It aims at enabling a comprehensive and broad base for modern data architectures. It is based on open source technologies. Another good thing about Pivotal Big Data Suite is that it can be deployed on-premise as well as in public clouds.

 

Hottest Big Data Technologies

  • Data Integration

Data integration is comprised of tools used in data orchestration throughout solutions such as Apache Pig, Hadoop, Apache HIVE, etc.

  • Data Virtualization

Data virtualization is a technology that relays information through different big data sources like Hadoop, and through distributed data stores in real-time and near real-time.

  • Predictive Analytics

Predictive analytics could be termed as hardware and/ or software solutions allowing businesses to find out, assess, maximize, and employ predictive models through the analysis of big data sources, in order to reduce risk and augment business performance.

  • Data Quality

Data quality is comprised of data cleansing and data enhancement products, delivering these essentials on large, high-speed datasets, through the application of parallel operations on distributed databases and data stores.

 

Big Data Trends

  • Big Data – Now More Approachable and Quicker

Hadoop is certainly useful to perform sentiment analysis and machine learning, however, businesses are often concerned with the speed of the interactive SQL.  This is because; SQL is a channel for businesses who intend to use Hadoop data for quicker exploratory analysis and recurring KPI dashboards. Big data has now become quicker and more approachable by embracing new and quicker database technologies such MemSQL, Exasol, Hadoop-based stores like Kudu, etc.

  • Businesses Demanding for Options Beyond Hadoop

Earlier, most of the Big Data based technologies focused on fulfilling the need for analytics on Hadoop. However, companies now are demanding for multiple options beyond Hadoop. Experts believe that platforms that date and source uncertain will tend to survive, while those built only for Hadoop and do not succeed in deploying across use cases may be ignored by businesses.

  • Big Data Investments

Yes, one cannot discount the significance of high-volume, high-variety, and high-velocity information assets. However, the most important aspect propelling investments into Big Data is the variety. Experts believe that this trend will continue to flourish, as organizations look forward to integrating additional sources and focus on the long tail of Big Data.

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