Big Data Overview in 2017
Big data has been transforming the way companies do their business for the past years or so. It is impacting some areas of our lives that we are not even aware of. We must understand that everything we do is leaving digital traces that companies gather and analyzes. They then use the results of this thorough analysis to make a decision on how to better reach out to people and improve their company’s performance as well.
Best New Products & Technologies Of 2017
We’ll give you the big data overview for 2017 and information about growth of big data. We have consolidated a short list of trends and products that emerged in the market for big data analytics and management.
Big Data Trends of 2017
- The NoSQL takeover
It has been predicted by IT experts that NoSQL and unstructured data will be significantly adopted in the year 2017. The shift to NoSQL databases as a top piece of the enterprise IT landscape becomes clear as the advantages of schema-less database concepts become more pronounced. Hadoop has been greatly utilized by more companies this year.
- Big data gets fast
Even though there has been a significant demand for data from users around the globe, Hadoop never lost its ability to perform faster data exploration.
- Availability of data and analytics tools to end-users
Self-service data processing tools are now exploding in popularity. This is in part due to the shift toward business-user-ge
Below are some of the remarkable big data analytics software for 2017.
- SPSS by IBM
IBM SPSS Statistics software features Predictive Analytics that can help you find new relationships in the data. Even without previous statistics experience, this software allows a user to easily access, manage and analyze data sets for sound decision making.
- SAP HANA by SAP
This Big Data system features in-memory technology, analytics database, and event processing Big Data system, which consists of in-memory technology, analytics database, and event processing.
- Ideata Analytics
Easy to use analytics tool provides users in preparing and analyzing big data sets. Its connections to numerous data sources such as Hadoop and Redshift, it provides users straight access to their data. Featuring drag and drop interface, users can swiftly picture their data and interactively discover insights in it.
Misconceptions about Big Data Management and Analytics
We must understand that the success in using big data is not just about an implementation of one technology. It requires putting together a wide array of technologies, big data service providers, and processes. You need to make sure that you are doing the right thing in every stage of big data analytics—from capturing, storage, cleaning, query, analyzing, and visualizing data. Seamless integration is very much needed for you to fully benefit from this. Lastly, the entire workforce of the organization must be fully committed to creating a data-driven culture and culture of being open to changes.
Big data is not just a trend. It is here to stay, and as we can see, its still growing and providing more opportunities for corporations to utilize it for their benefits. And as the years go by, let us look forward to more innovations to come!