Building a solid data strategy for your organisation

Building a solid data strategy involves considering a variety of important matters. These include ensuring that the entire workforce is on board, that data is tightly secure, and that the software at the company’s disposal is suitable for what needs to be achieved.

It’s vital that a balance is struck between innovation, realistic expectations and security when beginning to draw up such an initiative, as it’s bound to be a long-term commitment.

Prioritise employees

One way to ensure that your data strategy is a success is to build it around your employees. This will ease along data analytics operations, as well as reduce uncertainty.

“Organisations need a coherent data and analytics strategy in order to extract all of the insights they need to move the business forward,” explained Helena Schwenk, market intelligence lead at Exasol. “This means placing humans at the heart of the data strategy.

“The most effective data strategies are integrated from the get-go with the overall business strategy and establish common and repeatable methods, practices and processes to control and distribute data business-wide. With the whole organisation involved from the beginning, they can drive it forward.

“Data democratisation, as part of an organisation’s data strategy, then takes this one step further – giving employees at every level access to data insights that are relevant to their role. This level of buy-in across an entire organisation drives real cultural change by turning data analytics into a day-to-day contributor to the business rather than a perceived business function.

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“This allows employees to make better informed decisions and uncover new opportunities. Opening up data in this way also helps to overcome resistance or misunderstanding of data analytics by actively demonstrating how it can enhance an employee’s role and free up time for them to perform more value-add tasks.”

Consider the end goal

Digital initiatives can be susceptible to a lack of clear focus if short term and end goals are not set out from the outset. This can be aided by ensuring that the workforce is empowered to manage data.

Gary Richardson, managing director of emerging technologies at 6point6, said: “Instead of beginning with the data, start with understanding your business objectives. Consider the strategic aims you have both long and short term, and the questions you need answering if you are to achieve those aims. Here you are establishing what it is you need your data strategy to do.

“Ascertain what data you need to answer the questions you have. Define the ideal data that would serve your needs, and work out if your organisation has access to that data. As well as this, look beyond your organisation to find what data you could gain access to.

“In addition, you should consider the processes in place within your organisation. Do your teams collaborate and have access to data to make data-driven decisions? Your company must shift towards a process of working together across teams in a way that achieves common goals.”

Define hardware and software requirements

Richardson went on to stress the importance of knowing exactly what is required of the data storage technology your company has at its disposal, and building your data strategy around that.

“Your current data storage technology may not be suitable, or perhaps you can supplement it with cloud solutions. You may require additional or different analytic or reporting capabilities,” he said.

“Do you have a consolidated and integrated tech stack that allows you to make accurate data-driven decisions in good time? The architecture and infrastructure for complex use cases must be put in place and able to support your entire data and analytics lifecycle.”

Yasmeen Ahmad, vice-president, global business analytics at Teradata, weighed in by stating: “Any solid data strategy should include a technology architecture that supports innovation. The ecosystem of tools and technology must be plug-and-play to allow organisations to keep up with fast-paced technology innovation.

“Furthermore, the technology architecture should be designed to meet the scalability, robustness and reliability needed for AI and analytics solutions that may require real time execution and will inevitably become business critical.”

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Keep the tech simple

Staying with the specific technology available within the company, refraining from investing in anything new could go a long way in easing the process of building a data strategy.

Implementing a new plan such as this could be challenging enough without having to get used to how new technologies work.

“When it comes to technology, you need to simplify and standardise, making it easier for your data strategy to be applied,” said Greg Hanson, vice-president EMEA and LATAM at Informatica. “A standardised data management platform is key to this.

“There is no point in identifying an innovative solution for the market right now, only to find that it will take months to implement due to legacy systems, or the need for multiple skill sets and tools which have a direct impact on an organisations agility.

“Many organisations are faced with that situation right now, and they must act and redouble their digital transformation initiatives in order to avoid falling behind.”

Ensure sufficient governance

In addition to focusing on establishing realistic goals and building around your workforce, it’s important for your organisation to ensure correct data governance according to the current regulations.

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“A data strategy would not be complete without appropriate consideration of governance,” continued Ahmad. “There is increasing focus on ethical, responsible and secure use of data and insights by corporations, including new laws and regulations.

“The data strategy should outline the organisation’s principles, guidelines and expectations regarding the use of data. With analytics driving more autonomous and real-time decisioning, it is also essential for the data strategy to consider how analytical models and outputs will be governed to ensure they are free of bias, inaccuracies and bad decision making.”

Centralise data management processes

A final aspect of building a solid data strategy for decision makers to consider relates to how the data itself is managed.

Due to how quickly amounts of data can grow, it’s vital that control isn’t lost, and that it doesn’t become unorganised. According to Mike Kiersey, principal technologist at Boomi, this is where centralising data in one place can come in.

“Because a modern enterprise is a data-driven enterprise, the majority of companies will have several data management practices in place, from data migration to data governance,” said Kiersey. “What they often lack is a management tool to tie these together.

“Master data management synchronises your data systems through a single, as-a-service hub, breaking down disparate systems and silos to create a data strategy that is harmonised and flexible enough to adapt to shifting needs.

“By having a master data management hub, corporations tie their digital ecosystem together and they get complete visibility across the enterprise from a centralised point.

“A data strategy is now so much more than just storage: it should be an efficient, easily-scalable and agile tool to help organisations gain control of their most important asset.”


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Aaron Hurst

Aaron Hurst is Information Age's senior reporter, providing news and features around the hottest trends across the tech industry.