Creating faster, cheaper, efficient, cognitive, next-gen analytics and insight engines for enterprises of the future

Business relationships are becoming increasingly complex and interdependent as they expand across industries and borders. This generates a massive amount of non-linear transactional data, majority of which is siloed and un-rationalized across disparate legacy systems.

Such systems often have poor analytics and inferencing capabilities. This means that they do not provide real time insights. Additionally, real-world data is characterized by multiple entity relationships, multi-modality, spatiality, and temporal coordinates that do not get captured accurately in traditional data warehouses.

Therefore, the entire approach towards collecting, storing, and analyzing real-world data often does not suffice in today’s highly competitive and uncertain environment.

To meet the ever-changing needs of consumers, organizations need new ways to capture and analyze data, generate quick customer insights, in order to make the right decisions. New technologies like knowledge graph databases supported by AI/ML can help build solutions to address these challenges.

Building an enterprise brain can enable organizations to continually analyze latest situational data, determine optimal actions, execute them, and then track their impact. These capabilities can be customized according to an organization’s requirements, giving rise to brains tailored to each industry such as a telecommunication brain, a pharmaceutical brain or a retail brain. Wipro’s ‘Enterprise Brain’ leverages semantic knowledge graphs and semantic data catalogs in order to store and synthesize distributed datasets. This results in dramatic improvements in capabilities for analysis, reasoning, inferencing, predictions as well as for churning out usable recommendations from various enterprise data sources, both internal and external.