Big Data Analytics

TDWI developed this unique tool, the first of its kind, to help you determine the maturity of your organization's big data initiatives in an objective way when compared with other companies. Complete the assessment and receive a set of scores indicating your big data maturity across five dimensions that are key to deriving value from big data analytics: organization, infrastructure, data management, analytics, and governance.

Big data analytics is the application of advanced analytic techniques to very large, diverse data sets that often include varied data types and streaming data.

Big data analytics explores the granular details of business operations and customer interactions that seldom find their way into a data warehouse or standard report, including unstructured data coming from sensors, devices, third parties, Web applications, and social media - much of it sourced in real time on a large scale. Using advanced analytics techniques such as predictive analytics, data mining, statistics, and natural language processing, businesses can study big data to understand the current state of the business and track evolving aspects such as customer behavior. New methods of working with big data, such as Hadoop and MapReduce, also offer alternatives to traditional data warehousing.