Businesses today face a common dilemma: How does one make sense of all gathered data and transform them into useful insights that will help in decision making? Data’s prominence in today’s business processes has made it a core element in every organization‘s success. Companies should either keep up or get left behind as forward-thinking ones grab opportunities presented by the proper analysis and management of data.
Compared to previous years, there are now a host of modern technologies and techniques that can be used to serve customers and move businesses forward, making it a very competitive landscape. Instead of reacting after the fact, companies would do best to take a proactive approach and anticipate business needs and market trends so they can optimize outcomes. This is why organizations that create or gather data to use for decision making should rethink their data architecture or find ways to bolster it. Having data at your fingertips is one of the best ways business processes can be optimized so this must be considered when thinking about data architecture. Fortunately a modern operational data store (ODS) can help make this happen. By acting as an intermediary to a data warehouse, an ODS keeps operational data where it can easily be accessed whenever it’s needed.
Why Data Architecture is Important
An organization’s data architecture sets the standard set of tools used to manage data and defines the processes involved in the capture, analysis, interpretation, and delivery of usable data to users. These users and their unique data requirements are also identified by the data architecture. Ideally, it should set data standards for all users and data systems, providing a model of potential interactions between different systems and their users. A proper data architecture should also be able to define data structures used and how business applications use them. It also controls the flow of data by setting the criteria for data processing operations. A data architecture encompasses all data used by the organization, including data in use, data in storage, and even data in motion.
A data platform and data architecture, although often mentioned together, are essentially different. They are both used for the effective management of business data, but a data platform specifically refers to the tools and systems that move, shape, and validate data. Often, it’s used to refer to the underlying database engines and data assembly framework that allow data engineers to create usable datasets that will help the business predict and, to a certain extent, control outcomes.
Why Use an Operational Data Store?
If you’re wondering how challenging data analysis and management can be, just imagine how much work one has to put into storing, analyzing, and interpreting 2.5 quintillion bytes of data each day. This is why companies are now employing data analysis systems and strategies to help them predict business outcomes and achieve expected results. Companies that store large amounts of data in legacy and disparate systems, even those that use cloud-based data stores, suffer from the challenges of having multiple systems of record. This system affects data integrity, especially if the business employs digital applications in various environments.
Developing applications require high-throughput systems and reliable API’s so that workload is minimized and processes are fast and nimble. A modern ODS can act as a digital integration hub, enabling data integration and empowering businesses with data analytics. It will assist in the digital transformation of a business by helping migrate applications to the cloud and offloading and modernizing legacy systems. If your customers have ever experienced slowdowns while using your service or if applications find it hard to maintain efficiency during high user concurrency, implementing an ODS architecture is an ideal solution. It also adds value to any business due to its ability to provide reports, analytics, and business intelligence (BI) on fresh data and accelerate data ingestion and processing times.
The Modern-day Data Architecture
Modernizing an organization’s data architecture presents a multitude of opportunities to help the business through leveraging the power of modern data analytics. By harnessing the power of data and transforming it into something businesses can use, companies can create automated supply chains, predictive models for business processes and predictive customer service systems. An effective data strategy can be very challenging to implement quickly, and those that joined the game early on have the advantage of time and a system already in place. Organizations planning their own digital transformation, however, shouldn’t lose hope and use the big data momentum to move their data strategy forward. They should move away from the fear of disrupting business by implementing a new data architecture or modernizing an existing one and take a look at the opportunities that will open up by making their data work for them.