Automation has revolutionized industries and business for years. In the world of data, automation plays a well-honed role in rapidly developing modern data estates.
Before we proceed any further, let’s establish an understanding about the purpose of a corporate data estate. A data estate is the technical architecture and enterprise infrastructure that enables organizations to manage and consolidate their corporate data (relating to analytics, customers, social, business units, documents, apps and more) in a central data hub.
A data estate can be developed and deployed on-premises, in the cloud or hybrid and should allow you to connect to most data sources. From here, you can store, index, catalog, model, process, source, move, transform and document your analytics data for viewing insights, investigating historical data, predicting trends, producing reports, and making data-driven business decisions. With the central data estate in place, and the removal of numerous data silos, organizations can establish what’s known as “one version of the truth.”
Furthermore, the data estate should be architected so that you can easily absorb the free flow of incoming and future data so that the enterprise can easily move and model data quickly and efficiently. With proper design, businesses can designate expedited access to appropriate users for appropriate data, thereby enabling them to strategically account for governance, safeguards and privacy needs.
Regarding automation, generally speaking, there are many benefits to automating any process such as saving time, lowering costs, and simplifying tasks, to name just a few. With a strong track record for revolutionizing operations and systems, it should then come as no surprise that automation can have a significant impact on the development and management of a modern data estate. Saving time and money always sounds good. And when it comes to automating your corporate data estate, we’re not talking about saving just a few dollars or a couple of hours. We’re talking about significant savings.
Historically, building a data warehouse has not benefited from automation and instead relied on the manual creation of schemas, data, ETL processes, metadata, users and applications. To help achieve the build and deployment of an enterprise data warehouse, consulting teams were typically required—extensive billable hours and long development cycles were the norm.
Fast forward to today and we find a significant number of companies are benefitting from the power of automation. As more and more companies look to leverage the cloud for their modern data estate, they want a solution that is scalable, agile and future-proof. They also want a model that is expeditious, shortens and simplifies development, eliminates manual coding and repetitive tasks, and removes roadblocks that prohibit instant access to data. This can all be achieved with data automation.
By using a data management platform that automates the building of an analytics data architecture, businesses can provide their users with fully automated data preparation, offering them self-service data accessibility to maximize decision making, reporting, advanced analytics and AI.
Automation allows you to simplify the data preparation process, reducing the time it takes to model data. It allows you to operationalize the results of your machine learning process as part of your enterprise analytics environment and enables AI to do its thing.
Let’s take a look at how automation can help your business rapidly and efficiently build a modern data estate.
- Utilizing a data management platform can provide a cohesive data foundation for analytics data in the cloud, on-premises or a hybrid. You can do so by eliminating the need and time to manually stitch together tools for ETL, data modeling, code management, security, and documentation.
- With an automated data management solution, scripts are automatically generated and kept up-to-date to reflect the correct names of fields and sources that have changed. When a system keeps track of security, you simply add the person to the same security group, without copy and pasting access rights or manually keeping track. The system always provides an up-to-date overview of people who have access to every piece of data.
- Calculations are only made once and reused throughout the entire solution and in every front-end to access the data hub or data warehouse. Automated data impact analysis and lineage can bring clarity about the origin of data, without IT having to answer these requests by going through hundreds of lines of code manually.
- The automatic creation of documentation keeps track of which data goes where. Admittedly, you’re still stuck with the task of reading that documentation, but that’s another matter. But more importantly, you can help support efforts to satisfy various audit and compliance requirements.
- Automation allows for automatic detection of changes in the data structure, and keeps systems up-to-date, making maintenance easier, and the adding of new data sources significantly faster and more flexible. This means more time for staff to put data to good use. By automating all the repetitive manual work that has been typically involved, businesses free up employees’ time and the reliance on resources—saving countless hours—and allowing them to focus their attention on more critical business matters.
- There is no need to re-engineer when moving from legacy to new technologies. An analytics architecture built with an automated data management platform can handle variations in the underlying technology—meaning that moving from SQL to the cloud can be accomplished simply and quickly. The chores behind writing documentation, comprehending data lineage and maintaining security can become a thing of the past.
- You can easily populate a data hub or data lake with virtually any number and any type of data sources to fully automate a continuous flow of data in and out. To simplify and add to the data automation effort, organizations should consolidate, integrate and centralize all of their data sources into a central hub. All this results in a “one-stop shop” for all enterprise data and addresses the ongoing challenge organizations face on how to manage present and future data. It also means “one version of the truth” to help ensure consistency and data integrity throughout the business for all data users.
With automation, myriad hours of work by tech staff (and certainly external consultants) are substantially reduced. IT is freed from the responsibility of managing and performing those mundane tasks that can be easily handled with automation. IT can therefore become more of a supporting unit that empowers business users to leverage all the great and valuable information the organization has already stored as data, and all the new data that will flow into the company over time.
As laid out above, automation will improve an organization’s capability to use their data as intelligence for making better quality business decisions. The bottom line is this— by automating your corporate data estate, you’ll achieve better agility, faster access, and benefit from a holistic view of all your data.
