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The old way of managing data doesn't work

Read time 2min 50sec
A modern data stack drives efficiencies.
A modern data stack drives efficiencies.

Why do businesses struggle to unlock true value from their data? Norah Wulff, head of technology and operations at WeDoTech, highlights the key problems.

She says data initiatives often take too long to get off the ground, which can cause businesses to give up or change tack.

In addition, the promise of value of data warehousing projects is often lost due to other factors, including the fact that planning for the required hardware based on the estimated load and usage, is often a 'thumb-suck' exercise and requires a significant upfront capital investment.

"Too often, data requirements are restricted to lower the required storage and computing power. The opposite approach, where the company invests in high-spec servers, that handle a significant load for a few days a month and sit idle for the remainder of the time, doesn't work either."

Then there is a question of skills. "Finding and retaining the appropriate database administration skills to guarantee that data is readily available when needed, and indexed accordingly, is challenging and expensive."

Wulff adds the development of the processes to extract, transform and load the data into a data warehouse can be an expensive and onerous task too. "Maintaining these processes also requires a lot of time and effort, particularly when critical processes go wrong due to changes to the source systems or hardware limitations."

Unfortunately, the visualisations and insights that were sold to the business when it purchased its business intelligence tool of choice, becomes a distant memory when it has to wait three to six months to see the results, and these are often not what was expected.

However, she says with a modern data stack, companies can realise the value from their data initiatives faster. With a modern data warehousing approach, the traditional extract, transform and load process becomes faster, and more agile, where all data is loaded and then the relevant data is transformed into useful information.

"With new cloud-based technologies, businesses can work in an agile manner and get all of their data into a single platform without breaking the bank," adds Wulff. "Cloud data warehousing tools, such as Snowflake, allow companies to first test the waters to realise value in their data initiatives. Data pipeline technologies such as Fivetran enable businesses to bring all of their data into a cloud data warehouse platform. All that is required is a five-minute setup."

Then, she says once data has been blended into meaningful information, big data analytics platforms, such as Looker, allow organisations to embed data into every aspect of their business processes.

"Looker is way more than a data visualisation tool; it gives anyone in your company real-time access to data that drives your business. With a 360-degree vision of your business, you can finally ask sophisticated questions from your data to make better decisions and drive business value."

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