Data Driven Decision Making

By Charles

April 3, 2017

Database Services, SQL development

Most business decisions being made are data-driven.

If you see a massive demand for one SKU being sold, you buy more to replace it and meet that demand.

If you notice that 30% of those orders also included the same product, you could use that to justify a special offer to try and double those additional sales to 60% increasing your ATV (Average Transaction Value).

What is Data-Driven Decision Making?

Put use your available data to justify your next business move.

Do it right, and those decisions can lead to more significant profit margins but do it wrong, and your team can lose all faith in their choices and a load of money.

GIGO – Garbage In, Garbage Out

To have high-quality decisions being made, you need to have high-quality data to start with.

If your data is, at best, average, then your choices will be moderate. You need a decent-sized amount of data to dig through to find patterns.

The more data you have, the greater the probability of a good decision being made.

However, it is not just about the amount of data. It’s also about the quality of the data.

DQS – Data Quality Services

DQS is a service which comes with SQL Server. It allows you to cleanse, match and profile data.

It will enable you to edit data in your Integration Services packages and integrates with Master Data Services, allowing you to perform de-duplication on source data.

For Data Driven Decision Making to work well, you must remember that the data quality will determine the decision’s quality.

The data must be clean, relevant and fresh. If your data is old or stale, it will harm your decision-making.

For example, do not use January 2015 data to predict January 2017. Use January 2016 instead.

Call us or use our contact us page to discuss data quality issues.


About the author

Microsoft Certified SQL Server DBA with over a decades experience including work for large FTSE 250 companies amongst others. The SQL Server stack has been the focus of almost all of my career in IT. I have experience designing, supporting and troubleshooting large Data Platform deployments.

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