Ride the Wave
Gaining value from emerging data sources is nothing more than the next step in the data evolution.
Data is now available to organizations in a variety of forms and structures. Data is also available from emerging, information-rich sources like blogs, social media and mobile devices, which make advanced analytics top of mind for businesses. But is any of this really new? Or is it simply the next logical step in the evolution of data? Teradata Magazine sat down with Scott Gnau, president of Teradata Labs, for the answers and to find out how organizations can thrive in this era of rich and boundless information.
There’s a lot of talk about the plethora of data now available from new sources. But data sources have been expanding for years. Are we really just saying that everything old is new again?
GNAU: Based on what we’ve seen and how our existing, traditional market has evolved, I would say yes. Data warehousing, BI and OLAP, which are second nature to executives today, didn’t exist 20 years ago. What made those ideas ubiquitous were the business use cases that showed value, demonstrated ROI and highlighted how companies could improve the way they do business.
Data is now coming to us from new sources and in different forms—and we’re just now developing use cases that demonstrate how the new data sources can be leveraged to deliver business value. Once we define those cases, I predict that the hubbub around data volume will die down and people will get back to the business of generating value through analytics, just like they’ve been doing.
So today’s data growth—in volume and type—is just part of an evolutionary path?
GNAU: Exactly. It really is just more data, and the more you have, the more business value you gain by analyzing it. New classes of data are driving innovation in terms of effectively managing and storing the information. These classes are also driving new types of analytics that can better derive value from the data.
What’s really interesting are the new types of data from previously untapped sources and the new analytics that are being invented. Notice that I never used the word “big.” Big is certainly part of the challenge, but data always grows. Technologies like parallel computing have enabled us to handle those increasingly large volumes. Data sets have also grown larger and more complex, but the technology used to analyze them and extract business value has evolved right alongside the data.
Multi-structured data is continuously pouring in from sources like social media, mobile apps and the Web. Why should organizations embrace this data deluge rather than be intimidated it?
GNAU: Many experts say there’s more data being created this year than can be stored. That idea is a little scary for some people. But rather than focus on the amount of data, it’s more important to look at how we can optimize this new information to positively impact our businesses.
It’s certainly true that there is more data volume and variety now available to us than ever, but that shouldn’t change the way we think about our mission. We still have to ask, “How do I leverage the data to improve what I do?”
Can you give some examples?
GNAU: Path and graph analyses are emerging analytics that enable companies to understand a time series view of a customer interaction. While that’s a great benefit, what’s even better is being able to do that a million (or billion) times and then look at a heat map of those paths to understand how you can optimize the customer experience.
Or you can look at a graph to study the relationships between events, customers or vendors to see how they impact each other. This information helps you leverage the network, whether it’s social network, supply chain or components in a complex system. This was almost unimaginable five years ago, but it’s where technology has been heading.
How does Teradata support those analytics?
GNAU: We spent decades building and refining technology that allows our customers to keep their data in a form where it hasn’t been changed or modified. Customers can then expose that data in a relational format to end users for analytics.
Today, our new technologies more effectively gather, store, manage and analyze detailed data, which is unstructured and semi-structured. We have very good domain knowledge and expertise in building systems that enable our customers to turn data into value. We can also leverage other new technologies, algorithms and capabilities that we are either creating or are available from the open-source marketplace to create a unified data architecture. We’re leading the market in innovation, which gives our customers a competitive edge.
How does a unified data architecture help organizations extract more value from their data?
GNAU: An effective and comprehensive data architecture roadmap includes Hadoop components for massive storage, transformation, data cleansing and other kinds of activities. It also includes a discovery platform, which we deliver through Teradata Aster SQL MapReduce. The discovery platform enables knowledge workers with an existing skill set to gain access to Hadoop data and the new kinds of algorithms offered in MapReduce.
All of this technology needs to interact with and extend into an integrated data warehouse. Having new insights into the data is interesting, but it becomes truly valuable when you can deploy real-time decisions based on that knowledge. That last mile of delivery is extremely important, and that’s where the Teradata integrated data warehouse shines.