Collecting, preparing, managing and analyzing ever-growing volumes of data continues to be a challenge for business and organizations. Here are 10 tools and platforms for gaining value from big data.

Data analytics, long the obscure pursuit of analysts and quants toiling in the depths of enterprises, has emerged as the must-have strategy of organizations across the globe. Competitive edge not only ...

These top data analytics tools and software applications enable deep insight into business data, creating major competitive advantage. Written by eWEEK content and product recommendations are ...

This week CRN is running the Big Data 100 list in a series of slide shows, organized by technology category, spotlighting vendors of business analytics software, database platforms, data warehouse ...

Big data analytics is indeed a complex field, but if you understand the basic concepts outlined above—such as the difference between supervised and unsupervised learning—you are sure to be ahead of ...

Relational databases are well-suited to conventional data analysis such as reporting and classical statistical analysis (what you learned in the college Statistics 101 class, for example).

Another Gartner Study from 2018 reported that of 196 companies interviewed regarding Big Data and Analytics, ... to specific Big Data applications ... example, transactional data doesn ...

Applications; Big Data and Analytics; ... Given the many successful examples, it’s no surprise that the market for digital transformation services is forecast to top $800 billion by 2025.

Big Data is about the harvesting of raw data from multiple, disparate sources, storing it for use by analytics programs, and using it to derive value from the data in entirely new ways. In other words ...

Advanced analytics: It’s not enough to collect and process industrial Big Data—there also needs to be capabilities in place to analyze and interpret the data, potentially in near-real-time, to drive ...

For example, Data Discovery excels in ease of use, but allows only limited depth of exploration, while Data Science provides powerful analysis but is slow, complex, and difficult to implement ...

Every enterprise software vendor will tell you how hot and in-demand their products are, but the notion rings fairly true with respect to BI (business intelligence) and advanced analytics.