Más contenido relacionado


Más de Ajeet Singh(20)


10 top notch big data trends to watch out for in 2017

  2. All that was ‘hype’ related to the term big data years ago became a justified norm in the world of business this year.
  3. Data has become the new currency and the technologies now revolve around the concept of putting the big data into work and increase ROI through enhanced productivity and minimal risk.
  4. BI in the year 2017 The year 2017 will continue to witness massive growth of data both in terms of volume and variety. With this kind of growth, we will see a simultaneous rise of systems catering to processing data in more real-time.
  5. Here are the most possible trends around...
  6. Speed up Hadoop This year will witness a surge of organizations who will be willing to adopt big data stuff, Hadoop, and myriad Hadoop Solutions.
  7. With Hadoop, organizations of any size will be able to process large volume and variety of data using advanced analytics to dig valuable information and use the same to make profitable decisions. Speed up Hadoop
  8. However, speed has become an integral part of everything nowadays so adoption of faster databases like MemSQL, Exasol and other Hadoop-based stores Kudu had become imperative. Speed up Hadoop
  9. Also implementing OLAP on Hadoop technologies like AtScale, Jethro Data and SQL on Hadoop engines like Apache Impala, phoenix, drill accelerates queries and keeps to the pace. Speed up Hadoop
  10. Convergence of IoT, cloud and Big Data IoT generates large volume and variety of data and a huge portion of this data is deployed on the Cloud.
  11. Convergence of IoT, cloud and Big Data The data will reside in myriad relational and nonrelational systems that include Hadoop clusters to NoSQL databases.
  12. Convergence of IoT, cloud and Big Data So capturing data and analyzing the same from innumerable sources itself will be a pretty tough challenge and demand for analytical tools that have the capacity to seamlessly connect and combine a variety of cloud-hosted data sources will definitely increase.
  13. Convergence of IoT, cloud and Big Data And such tools will aid the businesses to explore and figure out the hidden opportunities in the data gathered.
  14. Using Big Data to enhance CX This year will focus on enhancing CX with the help of big data, by moving its way from legacy to the vendor systems with hard core system upgrades.
  15. Using Big Data to enhance CX It aims at doing so by analyzing data with self- service flexibility and deriving insights about the ongoing trends.
  16. Using Big Data to enhance CX People would be using the big data analysis to interpret the behavior of the customers and thereby enhancing customer experience and increasing the revenue by reducing the churn.
  17. Self-service analytics platform Self-service data prep will be mainstream in the upcoming year. The end users play a major role in shaping the big data.
  18. Self-service analytics platform The biggest challenge facing the world of big data is to make the Hadoop data accessible to the business users. However, a step towards achieving this goal has already been taken in the form of self-service analytics platform.
  19. Self-service analytics platform Agile self -service data preparation tools not only helps in data prep at the source but at the same time makes the data accessible in the form of snapshots for quick and lucid exploration. These tools are minimizing the barrier for late Hadoop entry and will gain traction in 2017.
  20. Deep Learning Deep learning revolves around machine learning based on neural networking and imbibes great potential in solving business problems. It aids the computer to identify the items of interest in unstructured data of massive volumes to deduce relationships without specific programming instructions.
  21. Deep Learning The algorithms cater to the domain of artificial intelligence mostly, which has the ability to observe the patterns and gauge and make decisions for complex problems.
  22. Deep Learning So, deep learning is mostly helpful for learning from massive volumes of structured and unstructured data and extracting meaning from them and patterns from big data. Organizations are bound to pay more attention to unsupervised training algos to take care of the heavy influx of the data.
  23. Data Warehouse is heating up in the cloud The death of data warehouse has been quite the talk in the Big Data world for some time now! The pace obviously has declined but we have been witnessing a major shift in patterns in this technology where Amazon is now leading with the concept of on-demand cloud data warehouse.
  24. Data Warehouse is heating up in the cloud According to analysts, 90% of companies who have already adopted Hadoop will be sticking on to their data warehouses and with the new upcoming, the customers can scale the computing resources and storage accordingly in data warehouse compared to the huge volume of information stored in the Hadoop data lake.
  25. Rise of Metadata Catalog The concept of Metadata catalog aids the users to discover and explore the relevance of data. They make use of tags to understand the relationships between data assets and also provides query suggestions, thereby minimizing the time to get hold of the accurate data.
  26. Data Virtualization This year will witness a strong magnetism towards data virtualization. Data virtualization unlocks the hidden concepts and conclusions from a large set of data.
  27. Data Virtualization Graphical data virtualization allows the enterprises and organizations to retrieve and manipulate data on the go, no matter where the data is residing and in which format.
  28. Architecture Matures Hadoop is just no more a batch processing platform but has upgraded itself to be a multi-purpose engine for ad-hoc analysis.
  29. Architecture Matures It has started to been used to for operational reporting on day to day basis similar to the way done by traditional data warehouses. This year, enterprises will cater to these hybrid needs by following use case specific architecture design.
  30. Architecture Matures The modern architecture would be mostly needs to be driven, and they will look forward to combining the data-prep tools like Hadoop Core and end user analytics platforms so that they can be configured and reconfigured as per the evolution of the needs.
  31. Government Scrutiny We can expect a lot of government interference in the way data is going to be handled in this year. Government scrutiny will be done on each and every data that are being used by the companies and various government departments.
  32. Government Scrutiny With the ever increasing variety and volume of data, there has been a constant rise in the rate of cyber attacks, so governments will have a hand in this big data concept in this year. Now all that we are waiting for is how this will be done and how it will impact us in the coming year.
  33. As said earlier that data has become the new currency and with the ever increasing pace of growing connected devices gargantuan volume and variety of data is generated. So big data is bound to play an extremely vital role this year and at the same time help the organizations to derive valuable insights that would shoot up their business to the new level of success. CONCLUSION
  34. Official Blog Link - data-trends-to-watch-out-this-year/ Mail us at: Contact us at: +1-877-284-1028 THANK YOU