Data has value IF you can analyze it, said participants at a big data analytics roundtable at the Premier Business Leadership Series in Las Vegas. In attendance were executives from some of the largest Communications companies in the world including from the US, Canada, Turkey, Japan, Australia and the Philippines as well as executives from leading edge companies like Accenture, Microsoft and Google.

SAS participants included big data heavy hitters Jill Dyché, VP Best Practices; Paul Kent, VP Big Data; and Scott Chastain, Senior Manager Big Data. Each provided thought leadership on big data strategy, big data challenges, and specific use cases. This made for a lively discussion with some interesting themes emerging.

Theme 1: All participants had a big data strategy that includes Hadoop. However, what differed was whether IT was driving this strategy or the business units were wrestling with the big data. For this group, it was pretty much an even split. And, there were definite challenges on the misalignment between IT and the business unit with no clear owners of the data. Plus, acquisitions over time make the data less trustworthy, thus creating a need for data management and data governance.

Theme 2:  Big data without analytics is just data. And, it is the analytics that turn this data into predictive and proactive data.  For some the need was for the customers of their customer’s and not just clicks or ad impressions. This data is HUGE and is changing. It includes text and voice and queries on this data can take days to get answers.

Theme 3:  Right time is better than real time, though some said real time was mission critical.  Data latency is clearly an issue and just the sheer volume of multiple sources and how to bring this all together is a challenge. This was definitely an area where the group was split. Technologies like Event Stream Processing are enabling organizations to act and communicate with customers in real time.

Theme 4:  Big data use cases are extremely complex. Hot topics included the Internet of Things/M2M, data monetization and digital marketing. All three generate hugely enormous amounts of data from machines, sensors, devices, websites, social media, call centers, network data, etc., etc. The IoT holds promise to make our world a more automated, connected and safer place affecting industries like agriculture, transportation and healthcare. Data Monetization will open up new revenue channels for CSPs, Media companies and the like. Much of this big data has value, so all the participants and every other company in the world are trying to figure out how to conform to privacy issues while making money on all this data. And, being able to perform true multiplatform marketing and synchronizing digital data remains a challenge, which these leaders are aggressively attacking.

Do these themes resonate with you too? How are you approaching your big data and analytics strategies?