Businesses today are increasingly looking to extract insight from the data they have access to in as near real-time as possible.
They want to rapidly gain the insight and intelligence they need to drive optimum customer experiences; faster time to value and a competitive edge.
However, to achieve this, companies first need to be able to blend analytical queries and transactional data. Otherwise, they are likely to be basing decisions on data that is anywhere from several minutes to hours or even days old, making it all but impossible to capitalise on many real-time and near real-time business opportunities.
Bringing the Data Together
Transactions and analytics typically form two distinct data processing arms within the enterprise. Transactions often involve the processing of records data in relation to regular operations conducted across the entire business and are designed for write, not query, speed. Analytics, on the other hand, process data from multiple transactional databases and are designed for query speed to provide organisations with insights based on specific questions.
Data often needs to move from transactional systems to analytics, increasing complexity and latency that slows the business down and can lead to missed opportunities. Transactional data processing is often limited in its ability to quickly perform analytic queries, while analytics data processing is often too slow to deliver valuable real-time insights. A transactional approach drives business operations, while analytics make the data actionable and bring out its value, empowering organisations to identify connections across multiple transactional databases.
According to an IDC study sponsored by InterSystems, 86.5 percent of organisations use ETL to move at least 25% of all enterprise data between transactional and analytical systems. And nearly two-thirds (63.9%) of data moved via ETL is at least five days old by the time it reaches an analytics database.2 This is a critical obstacle for most organisations that want to deliver the right customer experience at the right moment.
Businesses also face other hurdles on top of this, such as the need to support more data types, larger data sets and an accelerated path from analysis to action introduced by mobile users, IoT/sensor data, and constantly emerging trends.
This situation isn’t helped by the range of different data management tools businesses typically use. For example, companies often use several different database systems, which means the data is saved and stored in a number of different places and formats.
Companies now have the challenge of making sense of and harnessing that data and determining how to extract value from it by applying it to business operations.
Implementing a Modern Data Platform
A modern data platform lies at the heart of a data-driven business. A data management platform is a centralised computing system for collecting, integrating, managing and analysing large sets of structured and unstructured data from disparate sources at massive scale. It can support multiple use case scenarios and workloads with native data and application interoperability.
There are three central pillars of a modern data platform.
• It must support all data types and data processing (analytics and transactions)
• It must be scalable, flexible and interoperable
• It must be reliable, high performance and have zero latency
A consolidated data platform helps companies achieve their core IT-related business objectives, such as simplifying architecture, reducing cost, speeding innovation and streamlining operations.
Delivering Ultimate Data-driven Experiences
Before going any further, it’s important to identify your organisation’s data infrastructure needs. This includes understanding where your data resides, how often and by what means it is accessed, and how it is being analysed.
Companies no longer need to choose between having real-time access to data and their preferred method of analysing data. They can access data how and when they want and have the ability to make the data actionable in real-time.
Timely access to data can have a major impact on company operations and customer experience. As more and more data is generated by companies and their customers, it is important to be able to easily access and analyse this information and use it to inform business decisions. A modern data platform simultaneously supports analytical and transactional decisions and streamlines data infrastructure costs, driving more intelligent insights across the entire organisation.