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3 Easy Ways to Turn Data into Actionable Answers

3 Easy Ways to Turn Data into Actionable Answers

Early on in my career, I was talking with a customer in a meeting about performance. The customer said to me that they needed to get reports out faster. My response was to “buy more printers.” After a moment of silence, I explained to the customer that they didn’t need faster reports – they needed better analytics. Unless the reports are providing valuable answers that lead to actions, how fast you get them is meaningless.

With that one statement, the 30-minute meeting turned into a 3-hour discussion on the value of information and how to operationalize the data.

Here are three easy ways to turn your data into actionable answers.

1. Expand to more sources of data

Knowing what happened is information. Understanding why it happened is insight.

The first part of getting better answers is to capture more and better data about your operations. Adding sensor, social, or web browsing data will help you identify the “why” behind the “what”.

For example, retailers can easily report that sales are down for some apparel, but adding insights from social media data that illustrates a trend has passed can tell you why. Asking questions about trends earlier on may even reveal an indicator that a downturn is coming.

Adding IoT sensor data can show manufacturers that parts are wearing down ahead of their normal schedule and even show what other components are contributing to problems. Getting answers before the complications manifest themselves will keep you ahead of the hitches.

Teradata Vantage™ allows you to uncover real-time intelligence at scale, regardless of where the data is stored. Using QueryGrid and the upcoming Native Object Store features allows you to store the data where you need and have ready access to it for the answers to all your business questions.

2.  Extend and integrate the types of analytics you are able to utilize

If knowing why something happened is insight, then knowing when it will happen makes it actionable.

Of course, to understand when something will happen requires a much different set of analytics beyond traditional SQL. For that, you need algorithms such as N-pathing, predictive models, and affinity. Are your customers starting down a path that leads to churn? Are your packages about to encounter a delay due to issues with the distribution center?

The real business value and productivity gain comes when you do not need to move the data around your different systems, but instead simply add the analytics process to where the data already resides.

This is the natural evolution of Teradata’s solutions. By adding Advanced SQL functionality into the database engine and allowing machine learning and graph analytic nodes to be added directly to the environment, you get the most powerful functions without moving the data.

3.  Enlarge the audience who has access to the data

Moving from actionable information to operational answers.

One last way to get better answers is to encourage more people to ask different questions. By broadening access to your data, you gain new perspective on your business insights.

In the past, most reporting and analytics systems were geared toward the business users. Today, there are many more groups that can help analyze and interpret the data. There are also more diverse tools and languages available to assist you with the task.

Companies spend a lot of time, money, and energy to collect and integrate data. To then limit that data to only business users is a lost opportunity. When data scientists are allowed access to the data, they can utilize operational applications and AI algorithms to create more insight, opportunity, and targeted outcomes.

In the past, there were two obstacles to growing Teradata’s user communities. The first was limited tool and language support, and the second was the ability to operationalize the insights.

With Vantage, both of these challenges are addressed. The environment can now be accessed via a wider range of languages, most notably R and Python. These user communities can now work how they like, directly against data within Vantage. They are able to gain all the benefits and full parallelism. The ability to operationalize is enhanced via AppCenter – where you can easily develop, deploy, and manage new learnings. Within AppCenter, users can simply execute applications without having to understand or create the sophisticated underlying code.

Better questions lead to more complete answers; these result in transformative business outcomes.

Using more and different types of data will enrich understanding of your business landscape and allow you to respond to previously unforeseen challenges. When you are able to add a variety of analytic tools and engines, as well as the number of people who can work with your data, you can significantly increase the impact of your actions.

The good news is that now you can not only get better answers, but with Teradata Vantage, you can get them faster as well.
Portrait of Rob Armstrong

Rob Armstrong

Starting with Teradata in 1987, Rob Armstrong has contributed in virtually every aspect of the data warehouse and analytical processing arenas. Rob’s work in the computer industry has been dedicated to data-driven business improvement and more effective business decisions and execution.  Roles have encompassed the design, justification, implementation and evolution of enterprise data warehouses.

In his current role, Rob continues the Teradata tradition of integrating data and enabling end-user access for true self-driven analysis and data-driven actions. Increasingly, he incorporates the world of non-traditional “big data” into the analytical process.  He also has expanded the technology environment beyond the on-premises data center to include the world of public and private clouds to create a total analytic ecosystem.

Rob earned a B.A. degree in Management Science with an emphasis in mathematics and relational theory at the University of California, San Diego. He resides and works from San Diego.

View all posts by Rob Armstrong

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