Organizational assets are the lifeblood of any company. They provide the foundation upon which business decisions are made and how every one of their processes is executed.
In the digital age, data has become one of the most important assets of companies.
That said, data architecture is a plan that shows how an organization’s data will be stored, organized, and accessed.
It includes a description of the data assets and how they will be used to meet the information needs of the venture.
How Have They Evolved Over The Years?
Nowadays, data architectures are more complex, with a variety of data sources, both structured and unstructured, being used.
Data warehouses still exist, but they often coexist with data lakes, which store raw data in their native format for later analysis.
Data is processed in real-time, and its integration is done using various methods, including ETL, change data capture, and streaming.
In the past, businesses would filter and transform data before loading it into a data warehouse.
However, starting in the mid-2000s, the adoption of big data technologies led to the rise of data lakes.
They store raw data in its native format, which removes the need to filter and transform data upfront.
ELT data integration is an alternative to ETL that inverts the load and transform steps.
Why Are They Important?
A data architecture that is well designed can help an organization in many ways.
It can support data integration, which is the process of combining data from multiple sources.
It can also support data quality improvement efforts, which aim to ensure that data is accurate and consistent.
Additionally, a well-designed data architecture can enable the effective governance of data and the development of internal standards.
It may also include the physical infrastructure (such as databases and servers) and the logical structure (such as how data is organized and flows between different systems).
Strong data architecture is essential for supporting a robust data strategy.
What Are Their Benefits?
Data architecture is important for ensuring that data is always accessible and usable by those who need it while also protecting it from those who should not have access to it in the first place.
It is also relevant for enterprise organizations because it provides a blueprint for how data should be managed and organized.
By taking an enterprise view of data management, data architecture can help improve data quality, streamline data integration, and reduce data storage costs.
In a way, it also lets us see the potential value in data that can be used across multiple databases.
This allows us to make better decisions about how to store, manage, and make the most of it.
Is There Any Possible Risk With Bad Data Architecture Design?
An overly complex data architecture can be a problem because it can create data silos that are hard to integrate. This can make it difficult to do analytics.
One way to avoid this is to keep your data architecture as simple as possible. This may seem like a counterintuitive approach, but it can actually be more effective in the long run.
Simple data architecture is easier to understand and maintain and less likely to create problems down the road.
Conclusion
Data architecture is critical for any organization that wants to leverage data and make better decisions.
Well-designed data architecture will enable an organization to capture, store, and analyze data in a way that supports its business goals.
It also includes the hardware and software components of a data management system, as well as the organizational structures and policies governing how data is managed.
If you are looking for a company that specializes in data architecture modernization in Canada, look no further than our expertise here at Newcomp Analytics.
We help organizations tap into their data by leading with a mix of strategy and development expertise, using data science, machine learning, and AI.
Contact us today and let us help boost your organizational data assets in no time!
