More and more technology organizations are developing products for designing, implementing and deploying big data analytics models. Venture Beat brought this interesting topic to us in their article, “AI and big data analytics startup Noogata nets $12M.”
Big data analytics helps businesses and organizations make better decisions by revealing information that would have otherwise been hidden.
Meaningful insights about the trends, correlations and patterns that exist within big data can be difficult to extract without vast computing power. But the techniques and technologies used in big data analytics make it possible to learn more from large data sets. This includes data of any source, size, and structure.
The predictive models and statistical algorithms of data visualization with big data are more advanced than basic business intelligence queries. Answers are nearly instant compared to traditional business intelligence methods.
Thanks to artificial intelligence (AI), enterprises can collect, enrich and model data insights, forecasts and recommendations across departments ranging from sales and operations to finance and marketing. Until relatively recently, there hasn’t been an easy, no-code way to integrate enterprise data systems with predictive models.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
