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Can an organisation’s data achieve its full potential?

Wed, 13th Jan 2021
FYI, this story is more than a year old

Achieving the full potential of data continues to plague even the best organisations. It's clear what it can do - from identifying new revenue streams to improving customer service - yet many businesses still struggle to get the most from their data.

The key to innovating with data lies in integration. For many mid-large sized organisations, data is stored in siloed systems, which makes it difficult for professionals to make efficient and accurate decisions in a timely manner. Relying on outdated or incomplete data is a recipe for disaster and will present a substantial barrier to an organisation's innovation agenda.

Recent data strategies involve using cloud-based data warehouses and data lakes to provide the flexibility and increased availability required to keep up in the fast-paced market. Although this begins to address the problems related to siloed data, it presents another issue: how can valuable data from different systems and storage be integrated into cloud-based platforms at speed to meet business needs?

What is holding CDOs and CIOs back from providing real-time access to readable data that can lead to actionable insights, and how they can overcome these challenges?

ETLs fail to keep up with business needs

To combine and utilise data from different sources, organisations have traditionally relied on the extract, transform, load (ETL) process. However, the business agility required to truly be recognised as ‘innovative' exceeds the capabilities of ETL; moving data so that it can be governed, cleansed and queried can take up to nine months, by which time the data is outdated.

From the perspective of a business leader, decisions need to be made with accurate, up-to-date information in real-time. ETL simply does not allow this and is one of the root causes of frustration between business and IT teams. In modern business, it's an expectation for employees to be able to access data when they need it.

CDOs and CIOs are far too familiar with the impossible task of enabling the agile access to data and analysis using traditional processes. In many cases, by the time a manual ETL process has been completed, a business opportunity has been missed.

Know when it is time to change

Think of a data pipeline as a single machine, and different data sources represent cogs that make the machine work. However, traditional data solutions are not made to serve modern business purposes. Although businesses can always push these tools to the limit in a manual sense, the ROI will never exceed the value of automatically integrating multiple data sources in real-time for analysis.

Many IT leaders have looked towards Change Data Capture (CDC) to overcome this. By reading and replicating transactional data from less agile sources through data streaming, analysts are given a pool of real-time data to query against. However, streaming alone is not enough to prepare data for analysis – data in its original form risks cloud platforms becoming a “data dump”. Hence, true agility cannot be achieved if, once streamed, another manual process must be embarked upon to refine that information and prepare and provision it before it can be analysed. Automation is essential.
Automating these manual processes is essential. Minimising the need for human input for tasks associated with ingesting, replicating and synchronising data allows organisations to quickly make data ready for analysis. An innovative and effective leader is one that accepts when it is time to change.

Can your data keep up?

As businesses and customers adapt to survive in rapidly changing economic and commercial environments, the speed at which data is analysed is critical to a company's competitive advantage. As many business leaders have already come to realise, having real-time access to up-to-date data can make or break their success.

By building a clear picture with all their data, businesses are better positioned to make smarter decisions at speed. This simultaneously marks the shift from passive business intelligence to active intelligence, enabling accelerated business value for a truly agile and data-driven future.

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