Why You Need To Shift From Being Data-led To Data-driven
Business intelligence is the lifeblood of modern organisations. Collecting, mining, reporting and extracting relevant internal and external information to draw value and move your business forward is imperative. But it’s no longer enough for you to be reactively data-led – you must also be proactively data-driven.
With the sheer amount of data created every day, data analytics can go way beyond traditional BI to give you greater predictive decision-making power based on real-time insights.
Evolving existing BI technologies and strategies into a data analytics-based approach is crucial. This opens up the ability to discover new insights, inform conclusions, fuel predictions and support decision-making.
Making the transition can also be a major driver towards automation and artificial intelligence (AI) to fuel further business efficiencies. From the automation of repetitive data entry to supply chain and stock control – but leveraging these technologies means the need for clean, accurate and detailed data to base decisions upon.
To enable this new approach, having the right database at the heart of your organisation is fundamental. Less sophisticated databases can rely on pre-aggregated data, which hinders the quality of the insights that decisions are made upon.
If you’re using one or more BI tools and are looking to perform more advanced data analyses, a live connection to an in-memory database really delivers. It offers speed, efficiency, compatibility and real-time availability of information, which brings new possibilities. Running a live connection from a BI tool to an in-memory database means more complex analyses can be performed faster, away from the tool your viewing your queries on. A BI tool generates the query, sends it to your database, receives the results and then renders them in your chosen format – all in a matter of seconds on your raw real-time data.
There’s also no need for coding to activate a live connection, meaning users can dig deeper into the data straight away. Furthermore, built-in intelligent algorithms monitor usage and perform self-tuning tasks, so your database administrators are freed up to work on more high-value projects — which can increase productivity and reduce total cost of ownership.
A particularly beneficial use case of a live connection between your BI tools and an in-memory database is if you’re looking to gather predictive analytics.
