Why focus on Data Architecture?

Thinking tactically can often solve problems quickly and effectively. When it comes to data architecture, the approach is a little more strategic rather than acting reactionary. A data architecture is the blueprint for how data is stored, managed, and used in an organization. It defines the relationships between different data sources, how the data flows between those sources, and employs the data governance policies that govern how data is created and used.

A well-designed data architecture can help organizations to improve data quality, increase data access and usability, reduce data redundancy, and improve data security.

What's important in considering what your overall data architecture necessitates? Here are three practices you'll want to put in place within your overall architecture that really help define what needs to be involved.

• Data modeling: This involves defining the structure of data and the relationships between different data elements.
• Data storage: This involves determining where data will be stored and how it will be accessed.
• Data governance: This involves how well we can enforce the policies and procedures for managing data, such as data security, data quality, and data access.

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Why do we want to focus on the overall data architecture? There are countless reasons depending on your use case(s) but the most important include improved data quality, increased data access and usability, reduced data redundancy, and lastly improved data security.

As mentioned earlier, data architecture can help to improve data quality by ensuring that data is stored in a consistent and structured way. Without having a focus on data quality, you may as well save yourself the investment and build out data silos. In all sincerity, building data quality into your overall architecture will save you countless effort and cost later down the road. Data architecture can make it easier for users to access the data they need by defining the data flows between different systems. This could include ETL for building out an enterprise data warehouse, or even possibly looking at doing Reverse ETL. Data architecture can also help to reduce the amount of storage space required and improve the efficiency of data processing by identifying and eliminating duplicate data. This is always a major part in understanding why an enterprise data warehouse is important. Lastly, data architecture can help to protect data from unauthorized access and use by defining data governance policies. With little attention to data security, you put your business, employees, and customers at risk to attacks that can cost an immeasurable amount.

Data architecture is an important part of any organization's IT infrastructure. By defining how data is stored, managed, and used, data architecture can improve a number of different aspects of your business. So what do you do first? Start with a clear understanding of your organization's business needs. What data do you need to collect and store? How will you use that data? What should you do next? Involve others in the process. Rome wasn't built in a day and neither will your data architecture.

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