In 1979, Teradata began life as a collaboration between Caltech and Citibank. Today, this enterprise software group is all about redefining business intelligence tools and data management. The Teradata Database is now the Teradata Vantage Advanced SQL Engine, The name not only highlights the evolution of the company but also recognizes that tech consumers now expect more from their tools.

Data integration for business is vital, with sources ranging from on-premises databases to any number of SaaS apps. Collating and organizing that data with an effective ETL (extract, transform, load) tool is the first step towards gleaning profit-boosting insights. The next step is to look for the most powerful data analytics tools available right now.

Table of Contents

  1. What is Teradata?
  2. Improve Data Quality with 4D Analytics
  3. Improve Data Quality by Setting Business Priorities
  4. Improve Data Quality with a Unified Approach
  5. Improve Data Quality with BTEQ and SQL Commands
  6. Improve Data Quality with Powerful Partners

What is Teradata?

Teradata is a data management solution with a particular focus on analytics. It supplies a database or data warehouse, which the company itself calls “industry-leading”, and reviewers tend to agree.

Teradata uses the patented architecture MPP, which stands for Massively Parallel Processing. MPP allows more complex analytics problems to be broken down and then distributed by the parallel transporter for efficient workload management. The Advanced SQL Engine leverages this architecture, providing complete scalability. The Teradata Ecosystem Manager allows users to interact and create workflows via a drag-and-drop interface.

In terms of ease-of-use and pricing, Teradata receives reviews with similar scores to other data warehouse and analytics providers like Snowflake and Google Big Query.

The following sections explain how you can optimize Teradata to get the most from your business data.

1. Improve Data Quality with 4D Analytics

Businesses want timely and accurate data analysis. Teradata created 4D Analytics, which integrates Time Series with Temporal and Geospatial aspects to give a “when and where” answer for just about any question. Based on IoT Edge computer solutions, the goal of 4D analytics is to turn raw data into actionable analytics that an enterprise can immediately use for business optimization. How do you make sure your raw data is fit for purpose? By utilizing an ETL tool like to bring all your business data into one location, and ensure it's structured correctly to allow Teradata's analytics to go to work.

2. Improve Data Quality by Setting Business Priorities

One of the popular advantages of Teradata is that it doesn’t just have to trawl through your business data in the order it’s received. You or your data teams can set priorities or align workloads to manage your SLAs and system resources.

Administrators can access the Teradata Database Priority Scheduler. This feature lets them control resource allocation and prevents over-aggressive queries from seizing resources from critical workloads.

You can automate priority changes based on your own priorities or by allowing the tool to monitor CPU usage.

3. Improve Data Quality with a Unified Approach

Another of Teradata’s innovations is Vantage, a cloud-based data analytics platform that brings together data lakes, data warehouses, and other sources for potentially unlimited business intelligence. The detailed analysis can flag consumer/client behavior, changes in transactions, how apps are being used, and any deviations from normal or specified parameters. This produces rich yet speedy insights.

The goal of Vantage is to let members of any team across an enterprise easily access the insights they need. That’s why Vantage, like, runs a simple-to-use low- or no-code interface. homogenizes your data while Vantage tells you what it means - the best of all worlds.

4. Improve Data Quality with BTEQ and SQL Commands

The BTEQ utility within Teradata allows experienced data managers with some scripting experience to:

  • Create macros
  • Run DDL statements
  • Run DML statements
  • Deal with stored procedures

This gives administrators even more flexibility when running precise data-gathering tasks—creating tables of records for specific purposes or taking deep dives into data that previously was not a priority. Admins can also create tables with FastLoad and FastExport and transfer that data to flat files.

MultiLoad allows users to deal with up to five tables at once. Teradata uses a Relational Database Management System (RDBMS) to interact with tables. TPT can link Teradata utilities such as BTEQ and TPump.

The BTEQ utility also permits the inputting of standard SQL commands, and a period at the start of each command tells the system not to treat the commands as SQL queries.

5. Improve Data Quality with Powerful Partners

Teradata understands that its data management solution doesn’t solve every problem. That’s why Teradata partners with a range of other data integration providers. Familiar names include:

If your business wants to maximize the potential of your business data, using an analytical service like Teradata with's ETL tool means you're not missing out on any data gathering or collation, plus every scrap of data is used for report creation and insight analysis.


Teradata is a powerful big data tool, but it's completely scalable for businesses that want to start out small and expand their data management options as they go. Teradata’s current focus is on unifying data and gaining deep insights, something it calls "Pervasive Data Intelligence." Users can implement metadata with Ab Initio to monitor and understand the SQL jobs at hand for performance tuning.

Teradata only really shines with structured data, unlike solutions like Hadoop, which can manage large volumes of unstructured data. That’s why you need an ETL tool to manage and structure your data first.

How Can Help with Effective ETL

Effective data warehousing is only as powerful as your data collection and data integration tools. An ETL tool is more efficient than ELT (extract, load, transfer) as it doesn’t rely on the resources of your own data warehouse to run the transformations. An effective ETL processing tool works on any OS—from Unix to Windows—via its own cloud-based platform. provides well over a hundred data connections to SaaS apps, data stores, and source systems.

If you would like to find out more about how ETL and business intelligence tools work together with data warehouses to create an unbeatable suite of data management tools, get in touch with our team today.