Breaking the marketing mold with machine learning

whitePaper | November 15, 2019

We are living in an era of digital disruption. Multiple industries are being disrupted, or fear being disrupted in the near future. Business models are evolving to cater to the dynamic markets and digital transformation that seems to be the answer to changing business models. Digital transformation is rapidly becoming a key priority in most industries, as organizations adapt to changing markets by leveraging technologies to build IT-centric business models. In general, organizations are using digital transformation to reach their goals of achieving greater agility, improving operational efficiency, improving customer experiences, and developing new revenue streams.

whitePaper | May 26, 2022

Since their invention in 1970 by Edgar Codd, relational databases have served as the default data store for almost every IT organization, large or small. Today, the most iconic and familiar relational databases include IBM DB2, Oracle Database, Microsoft SQL Server, PostgreSQL, and MySQL.

whitePaper | January 11, 2023

The world of master data management (MDM) is a complicated place to navigate and its native speakers use a language sometimes only they themselves understand. It is packed with complex descriptions, esoteric lingo and acronyms.

whitePaper | October 18, 2022

We talk about striving to be data driven. But in doing so, we’ve skipped an important step. Today, we must first aspire to be data-sharing organizations. That means becoming businesses where data is easily and proactively shared with every relevant person. Otherwise, there will be no driving possible. We’ll be left in the dust, lacking the gas — the data — to fuel us ahead in the digital economy. Gartner® said, “According to the Sixth Annual Gartner Chief Data Officer Survey,1 respondents who successfully increased data sharing led D&A teams that were 1.7 times more effective at showing demonstrable, verifiable value to D&A stakeholders.”

whitePaper | June 10, 2022

The past few years have witnessed exponential growth in data volumes, forms and sources of data. To handle this ever increasing complexity and dimensionality, an Intelligent Framework for knowledge discovery is required. This framework should also support text analysis, visualization, intelligent search, man-machine interface, data management, geo-spatial, temporal data processing including statistics processing. A holistic approach based on Artificial Intelligence and Advanced Analytics provides such a framework. It brings forth a breakthrough natural language-based cognitive technology, which provides instant access to powerful predictive and visual analytic tools for businesses in general and market research in particular.

whitePaper | June 24, 2022

The reactive approach to discovering, analyzing, and correcting data quality issues in business applications has been marginally effective throughout the era of data consolidation for analytics (data warehousing, etc.) and the subsequent onset of “big data.”