Gaining More Value from Big Data - 6 Key Takeaways from Data Summit 2016

Jun 8, 2016

By Joyce Wells and Stephanie Simone

Data Summit 2016 in New York City drew IT managers, data architects, application developers, data analysts, project managers, and business managers. Analytics, search, machine learning, and IoT were some of the key topics of discussion in educational presentations on industry trends and technologies, keynotes, and hands-on workshops at the conference.

Here are six key takeaways from Data Summit 2016 presentations:

Combining advanced analytics with machine learning: By taking a traditional approach to analyzing data, which includes defining the business challenge, data preparation, extracting data, ingesting it, building the model, deploying it, and then visualizing the results, companies can stay on top of its information. SQL can bring all these tools together for a complete analytics picture of an organization. - Satya Bhamidipati, director of business development of big data and advanced analytics at Oracle
The value of in-chip analytics: In-chip analytics is simpler for business users and IT, enabling ad hoc data mashups faster and at greater scale gain more value from data. – Jeremy Sokolic, vice president, product, at Sisense
The ease of search: Enterprise search helps users to find and understand information, structured and unstructured content. – Jana Mikovska, senior consultant at Raytion
Getting value from IoT: As more connected devices come online and generate more data, the hurdle will not simply be getting the data from the devices; the big challenge will be integrating it and using it for meaningful advancements. – IoT panel discussion with John O'Brien, principal advisor of Radiant Advisors; Joe Caserta, president and CEO of Caserta Concepts; and George Corugedo, CTO of RedPoint Global
Combining structured and unstructured data: By leveraging enterprise search, users can tap into relevancy within data, processing text and unstructured information, perform content extraction and linguistic analysis, extract entities to generate structured data, and handle security. - Jana Mikovska, senior consultant at Raytion; and Sebastian Klatt, vice president of business development at Raytion
The future lies in cognitive computing: These are systems that are programmed to learn, adapt, and discover with us. Industries are beginning to look at cognitive computing as a necessary business competency to deal with existing challenges. The gathering of massive amounts of data requires that humans have more assistance; and achieving the greatest value in unstructured data requires machines help with analysis. – John O’Brien, principal analyst and CEO at Radiant Advisors