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The Evolution of Operational Data Stores

Organizations today use insights driven by data to gain a competitive advantage. However, it is often a struggle to find the appropriate storage for this data. By using an operational data store (ODS), they can extract data across numerous systems of record and integrate it into a single entity. Traditional operational data stores have a number of limitations and next-generation stores have evolved to deal with issues such as latency scalability and speed. 

What is an operational data store?

Currently, many organizations manage data by using various systems of record. When they report separately on each system, an overall view of data is lacking. An operational data store solves this problem by extracting transactional data from systems of record and integrating them into a united repository that supports tactical decision-making. 

As the data comes from more than one system, the ODS is like a staging area where integration involves reducing redundancy, clearing out junk and checking data for integrity. 

An ODS is not for handling large amounts of historical data like a data warehouse and is not used for complex queries. It only holds a small window of current data for simple queries. As it delivers the best available instance of a data element at any given moment, it supports operational decision-making. 

Some benefits of an ODS

An ODS has many benefits for organizations by providing an overall perspective on operational processes. 

The ODS offers an updated view of the status of operations, making the process of diagnosing problems simpler. For instance, in a product delivery company, service representatives would be able to locate a customer order and its status. They could troubleshoot information without having to go into component systems. 

An ODS can automatically alert a financial institution about an account withdrawal through using time-sensitive business rules. These rules can automate processes and significantly improve efficiency. Not having access to current, integrated data would make attaining more efficiency unlikely. 

As an ODS does not contain historical operations and data, it is a secure option that is resilient to cyber-attacks and offers data privacy. Access to systems of record is often restricted, whereas an ODS allows for wider reporting capabilities within an organization. 

Its practical, structural design allows organizations to query data close to real-time operations, which gives them the opportunity to make sound decisions and can give them a competitive advantage.

Limitations of the traditional ODS

The concept of the ODS is not new but it is evolving all the time due to technological advances. Traditionally the ODS was refreshed on an hourly or daily basis for operational reporting. When organizations begin to transform digitally, a traditional ODS poses a number of challenges. 

One of the problems is that a traditional ODS does not offer real-time API services. It cannot meet new digital application requirements. 

 Another problem is that traditional database systems experience high latency when handling big amounts of data. 

User concurrency is a problem when using traditional databases, which offer limited scalability. Performance suffers when many users concurrently access the data store. 

As data is only refreshed periodically, the traditional operational data store means data reporting is not real-time. This may be suitable for day-end reporting but not for digital applications that need real-time data. 

Digital transformation is essential

Many traditional industries still use mainframe and other legacy data platforms for their systems of record. They have to compete with technology companies in sectors such as Fintech, which are unencumbered by legacy infrastructure or processes and have come up with new, more flexible business models and services. 

New regulations and more demands from customers are putting organizations under pressure to start modernizing. The world of work has changed considerably. For instance, remote working has become far more popular. Virtual office trends show that they are fast becoming an alternative to the conventional office setting in companies where technology enables employees to work from anywhere. 

Artificial intelligence, machine learning and the Internet of Things are transforming the way people work. Applications are exploding and with this, an evolution in the ODS has become necessary. Companies need to embrace digital transformation or they could be left behind. 

A next-generation operational data store

Organizations that do not have an ODS can use a complete next-generation ODS solution with all the necessary components. This typically includes a high-performance ODS and compute engine, event-driven architecture, analytics, smart caching and microservices API.

Companies that have existing databases can use an in-memory data grid so they don’t have to be replaced. Insertion of a distributed in-memory core between back-end systems and the API management layer deals with many of the challenges related to a traditional ODS. Peaks in user volume don’t impact performance. Back-end systems aren’t affected and customers have the quick response times they expect. 

It is possible to add the layers that are missing to a traditional ODS to create a next-generation ODS. This provides organizations with real-time processing of data they need to support new digital applications. They have high availability because the API layer is decoupled from the systems of record and applications will keep working even when a system of record is not available. This is essential today as customers want 24/7 service. 

Organizations also experience operational efficiency all the time, despite any peaks in volume. They can make better business decisions, too, because they have access to real-time data and can base predictive modeling on insights from it. 

With more and more organizations using cloud services, a next-generation ODS can offer them the flexibility they need. It can deal with hybrid deployments whether businesses have data on-premise, in the cloud, or a combination of the two. 

A final word

By implementing a next-generation ODS, organizations can overcome the limitations of a traditional ODS. A next-generation ODS offers scalability, low latency, fast performance and high availability. Making transformations like this enables organizations to thrive in a competitive landscape. They can make better business decisions that allow for improved productivity, more customer satisfaction and more profitability.

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