Data is the lifeblood of organizations, bringing information to various departments and functions. Keeping data healthy can be simple with good hygiene, but this is easier said than done.
We often say, “Information used is information in need.” “Information used” does not mean that said information is governed or cleaned, but rather that it could provide an executive specific insights -- like trend analytics -- for decision making.
The Customer Success function is relatively new to Teradata. In the Australian and New Zealand region, the Customer Success function started in 2020 with a primary focus to be a team of trusted advisors, helping customers maximize their investment in Teradata. Customer Success is measured around three focus areas: (1) customer relationship, (2) usage of their Teradata investment, and (3) the adoption and augmentation of new Teradata features.
Customer satisfaction plays an important role in customer relationships. We recognize that customer satisfaction is both qualitative and quantifiable. As each customer is unique, the approach we take is to work with the customer to define appropriate customer satisfaction metrics.
The Customer Success role is committed to maintain and enhance customer relationships through regular health checks with business and IT stakeholders.
Teradata was founded in 1979. Decision makers may unconsciously have a bias that this means that Teradata is no longer current as it is old technology. On the other hand, the statement that Teradata has been around for over two decades provides an assurance of sturdiness and reliability in the platform.
It is our privilege to change the old technology bias around in my role as Customer Success Manager, especially when we can show the customer the hidden strengths of the Teradata product that they have bought.
For example, in Q3 2020, we had the pleasure of hosting several SQL Q&A sessions to an audience mostly consisting of Teradata users that have worked with the product for over 10 years. The attendees came out from the Q&A session highly satisfied and pleasantly surprised with new and updated knowledge about the advancement of Teradata SQL incorporating Python and R languages.
Participants learned that if the SQL script was structured correctly, the user would no longer need to write lengthy complex scripts. Instead, they could utilize the power of the database to return the relevant information rather than a full data extract from the database. Teradata Optimizer is the feature that will find the most efficient way to return the SQL request automatically.
Another customer of ours commonly augments the database with datasets from spreadsheets. This is done through an IT change request which could take weeks to deliver. Their lightbulb moment was when they discovered they could write SQL on their Teradata database, whilst calling the spreadsheet from their data lake – realizing immediate productivity gains.
Teradata’s flagship product, Teradata Vantage, is the only cloud data analytic platform that offers a wide variety of features and capabilities. These features allow users of the platform to analyze data from different perspectives: predictive, prescriptive, and descriptive.
Teradata allows the use of data science languages within their SQL, such as R and Python. The use of Jupiter Notebook as a workbench is also permitted in the Teradata ecosystem. Teradata integrates with different visualization tools like Tableau, Qlik, and PowerBI, just to name a few.
The power of Teradata is in its ability to perform massive parallel processing, its robust data processing engine with its optimizer, and a mixed workload management system. Teradata Vantage offers these capabilities by default.
As Customer Success Managers, it is our role to ensure that Teradata customers are familiar with the various features and capabilities of Teradata Vantage. The above is just a subset of what Teradata can offer.