Tue. Sep 29th, 2020

How To Maximise Data Productivity To Achieve Success

Why Becoming A Data-Driven Organisation Should Be A Priority Is your company invested in data?

Why Becoming A Data-Driven Organisation Should Be A Priority

Is your company invested in data? With volumes of data growing exponentially, it’s time to make data productivity a key focus.

Worldwide data is predicted to grow by 61% between 2018 and 2025 according to a recent report published by the IDC. The base line of 33 zettabytes of data was taken in 2018, but we’re expected to generate a global 175 zettabytes in the following seven years. However, the creation of data is not the primary concern for business leaders, as instead companies need to focus on using this data productively for the benefit of their individual organisations.

Industry giants such as Coca Cola, Netflix and Amazon are already capitalising on the success of their approach to handling data, yet in a report written by New Vantage Partners, it was revealed that only 31% of market leaders have already become data-driven organisations. This leaves the majority of C-technology and business executives from companies such as General Motors, American Express or Ford Motor lagging in terms of data productivity. Although many major corporations such as these are reporting large investments into big data and artificial intelligence, they could also benefit enormously from taking a keen look at their current data setup, starting with the raw foundations of their data productivity.

In-Memory Databases

The success of your data productivity will always be dependent on having a quality database in place to handle the workload. When comparing in-memory databases, you’ll have unique criteria that you require to fulfil the needs of your teams. This is why many organisations opt for the creation of a bespoke database capable of handling the workload. When looking at specs, make sure that you take the following factors into account: cloud-readiness, IoT-readiness and ACID-complianceto ensure that the data remains accurate and consistent even in the case of failure.

Stream Processing

The introduction of 5G is set to increase both the volume of data and the speed at which it is streamed across our networks. This is likely to put pressure on our traditional data architectures. However, IT professionals can plan for this eventuality by prioritising stateful stream processing, which requires the minimisation of ingestion, processing and storage down to a single layer incorporating serialisable ACID transactions. To learn more, you can read a detailed break down here.

Investing in Analytics

The only problem with big data as a concept is that generating huge amounts of data is useless unless you have real-time analytics in place to make sense of the information output. In fact, your company can even leave itself open to fraud if you haven’t invested in analytics to detect any anomalies within your data sets. However, the use of analytics in your applications is also essential in order to improve internal manual processes as well as enhancing customer relationships by using data for increased brand loyalty. Analytics needs to occur within just a few milliseconds to benefit the end user, so your database must be capable of working within a tight latency budget.

With data volumes growing exponentially, if your organisation wants to remain at the top of its game, it’s time to invest in data productivity as an absolute priority so you don’t get left behind your competitors.

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