Operational Data Store Best Practices

An operational data store (ODS) collects data from multiple sources into a central database for reporting purposesIt helps businesses to make more informed, tactical business decisions.

The availability of the ODSthe accuracyconsistency of the data it provides can have a significant effect on business decisionsThis is why using best practices when implementing an ODS is importantThere are various questions businesses need to answer if they want to get the best use out of an ODS.

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What is an Operational Data Store (ODS)?

An ODS integrates data from multiple different systems of recordIt contains the most current data from the different systemsallows for more comprehensive reportingData in the ODS is refreshed on a daily or hourly basis or even on a more frequent basis to offer a real-time or near real-time viewThe data in the ODS is optimized for making simple queries on small sets of data.

A Modern ODS

A traditional ODS has a number of challenges, especially for businesses that want to use digital applications because they require scalability, speedagilityIt is usually based on a relational database which is an issue when handling large data amountsneeding low latency.

A modern operational data store solves these problems, providing the performance, low latencyscalability that digital applications require today.

A modern ODS offers fast access to real-time dataThe API layer is decoupled from the systems of recordthis means applications are available consistentlyfunction even if one system goes downHigh availability is crucial today when customers expect quick responses.

Infrastructure can scale to accommodate peak volumesback-end systems aren’t overloaded with excessive workloads.

A distributed in-memory core means many users can use apps concurrently without this affecting performance.

Identify Why an ODS is Required

Organizations need to identify reasons why an ODS is necessaryHere are some key reasons for needing an ODS.

It is unproblematic to handle huge data transactions as it does not involve a large amount of historical data.
Reports are more comprehensive when they are based on an overall view of data than when based on separate systems.
An ODS helps with real-time analysistactical decision-making as it offers a current snapshot of data available in a central repository from the different systems of record.
Only a few people have the security to access source systemswith an ODS, more people can have access to generate reports as it does not contain all the historical data, which makes it resilient to data hackingcyber attacks.
Integrated data from source systems offer a better picture of the customer as it includes data like support history, contact details,order informationThis enables better customer service, an essential requirement to remain competitive today.
Back-uprecovery are effortless due to the small size.
By increasing operational efficiency, an ODS helps to reduce costs.

AnalyzeUnderstand Data Needs

Understanding company data involves answering various questionsDifferent businesses require different solutionsso it is important to understand what data sources matterWhat existing tools are in place to collectanalyze data? Are they sufficient or not? Which data needs to be highly availableaccessible? If the business requires real-time analytic insights from data, how will they be used?

Decide on Degree of IntegrationTransformation

The ODS should be designedbuilt based on the functional requirements of the businessThe data in an ODS is subject-oriented, which means it relates to a specific area of business.

In order to get maximum value from the data in an ODS, it must be clean, accurateconsistentThis means it goes through an ETL process (extract, transform load) as it comes from all the different sources so it is in a meaningful format for useSystematic business rules must be applied to it based on the policies for data control.

Find the Best Method of Implementation

Industries like healthcareeducation still use legacy platforms. Big data in healthcare is an issuechanges need to be made but it is difficult for companies to discard what they are usingstart from scratch.

It is not necessary for businesses to rip outreplace what they are already usingIf they have a traditional ODS, they can augment it with missing layers such as event-driven architecture, a smart cache, analyticsmicroservices APIs.

An agile approach is an iterative one that allows solutions to evolve in response to business requirementsfocus on current business problems.

Businesses that are not already using an ODS can deploy a solution that includes all the components they need.

Decide How Important Real-Time Analytics Are For The Business

A traditional ODS is usually refreshed on an hourly or daily basisHowever, today’s need for real-time data makes this inadequateThe question businesses need to answer is what the ROI of a real-time refresh will be versus a less frequent update of the ODSReal-time refreshing is more expensive but it allows organizations to take immediate actionit is therefore extremely useful in situations where timely action is required.

The Internet of Things (IoT)mobile devices make real-time analytics importantenable businesses to react to data soon after it comes into a systemThis makes it possible for businesses to predict a problem, such as when a device may failtake corrective action before it happensReal-time reporting also helps with things like analyzing trade risksdynamic pricing.

Conclusion

A next-generation operational data store has many benefits in terms of scalability, agilityhigh availabilityBest practices when implementing an ODS include deciding why it is necessary, analyzing business databeing guided by functional business needsBusinesses need to decide on factors such as how current the data in the ODS needs to bethe degree of transformationintegration they requ