Database sizes are growing all the time for many different reasons. A prediction from Cisco is that $14.4 trillion in potential value will be created over the next decade as companies all over the world embrace the Internet of Things. To reap its benefits, companies will need to monitor and manage networked devices and be able to quickly analyze new data stores to keep making improvements and grow profitably.
The demand for low latency, speed and scalability is increasing all the time. Developed to help enterprises solve the data challenges which are present across all industries and organizations, an Operational Data Store can be a real benefit, especially a new generation one that deals with some of the challenges experienced when using a traditional ODS.
What is an Operational Data Store?
Businesses and consumers want to have access to real-time data that can come from a variety of places. An Operational Data Store provides the means to integrate the data coming from different sources. The ODS puts the data in a consistent format, while business operations are occurring. It, therefore, provides an operationally authoritative data source.
An ODS is not a new concept. Its main benefit is the integration of data from various systems of record for the purpose of reporting and analysis. This enables business owners and employees to make more informed decisions due to having a comprehensive view instead of the siloed view provided by each individual data source.
An ODS also allows more people to have reporting capabilities as systems of record usually restrict access to a few people for security purposes.
Where a traditional ODS can fall sort
When organizations start with digital transformation, a traditional ODS can pose some challenges. For instance, a traditional ODS does not offer real-time API services. It is usually based on a relational database, which can have difficulty handling a large quantity of data.
Applications that demand low latency are not supported and limited scalability can be another challenge. When multiple users access the data store at the same time, it can affect performance.
The refresh rate of a traditional ODS is not a problem when it comes to day-end reporting but is not good enough when it comes to digital applications. In this case, real-time data is necessary.
How Operational Data Stores have changed
A traditional ODS has a number of disadvantages, such as the fact that it is refreshed on a daily basis and only stores data for a short window. With the introduction of real-time digital applications, the traditional ODS has had to evolve to allow businesses to meet the challenges of limited speed, scalability and agility.
New digital banks and insurance companies keep moving away from legacy processes and infrastructure. They are innovating all the time when it comes to the models and processes they use. They need a new generation ODS to serve their purposes.
Only a small percentage of traditional finance organizations are currently managing to turn large data volumes from different transactional systems into financial analytics with usable insights. Insights can remain buried within the data and decisions may be delayed or made on the basis of static reports rather than real-time data.
Even well-known investment management or trading platforms can have data gaps and an ODS provides an ideal solution. Data silos can present a serious challenge that hinders user accessibility and give different versions of the truth depending upon which data source an employee is using. An ODS eliminates data silos and creates a single version of the truth.
Many industries such as healthcare, education, retail and transportation are still using legacy platforms and they will need to make some changes to stay competitive. Those using a traditional ODS do not necessarily need to replace it. Augmenting it with various missing layers is a possibility, such as implementing event-driven architecture, analytics, a smart cache and microservices API.
Benefits of using a next-generation ODS
A next-generation ODS offers the speed, scale and agility not available with a traditional ODS and that is so important when it comes to new digital applications.
Fast performance and low latency: Making API calls to various data sources for every action makes real-time processing impossible. Customers, therefore, do not have the response time they expect today.
Customers can benefit from quick response times with the use of a distributed in-memory core. Back-end systems are not affected by unexpected volumes or unplanned loads. Customer experience is the new brand and forms the core of any marketing strategy so you cannot afford to go wrong there. Companies can maintain customer experience at times when volumes peak and not over-provision expensive resources when they fall.
Better predictive modeling: Predictive modeling is made easier when real-time data is available for analysis.
More availability: The chances of one system going down increases when it is necessary to manage many systems of record. Decoupling the API layer from the systems of record means the applications continue working even when a system of record is not available.
Synchronize remote data centers: Worldwide organizations often have data centers in remote sites because they need to adhere to certain regulations and have high availability. A next-generation ODS makes it possible to synchronize these remote data centers in real-time.
Data on-premise and in the cloud: Many businesses today have a combination of data on-premise as well as in the cloud. This is not a problem for the next generation ODS as it can deal with both without impacting production performance.
Quicker time to market: A next-generation ODS can reduce manual schema mapping that takes weeks to a single click. Microservices architecture enables bringing new services to market more speedily.
Modernizing architecture with a next-generation ODS will help drive digital transformation and offer an improvement in throughput, availability and scalability. It offers more flexibility for running business operations, migrating to new business models and is a smart choice for upgrading operational capabilities. When they become more efficient and productive, companies can remain competitive and profitable.