More than nine out of 10 businesses are investing in data analytics and AI at an accelerated pace, according to Harvard Business Review. And, nearly nine out of 10 businesses (88 percent) are experiencing “greater urgency” to invest in data analytics and AI tech — with three-fourths of organizations doing so out of fear of disruption from a more data-savvy company.
The good news for enterprises prioritizing their data strategies this year and beyond is modern analytics products have never been as advanced or accessible. The challenge becomes, then, evaluating the data analytics offerings on the market to figure out which is the best fit for your company based on its needs, goals and budget. Choosing the right product is key to maximizing return on investment — and avoiding disappointing misalignment between expectations and reality.
Choosing a “winner” from the plethora of analytics platforms out there is a complex process, but here are some questions worth asking when you’re exploring options for your business.
What Capabilities Are Needed Based on Our User’s Requirements?
A key consideration is who will be using the data analytics software you deploy, as this informs the capabilities you should be looking for in potential solutions. For instance, is your enterprise aiming to democratize data access by connecting nearly all employees — even those in non-data-specialized roles like marketers — to tools through which they can query data and build interactive charts? Or are you searching for a higher-level tool meant for specialized data scientists and analysts?
If an organization is trying to de-silo and democratize data, ease of use is paramount. With a little training, users should be able to ask questions, then create and interpret visualization models without requiring intervention from more specialized teams.
As one expert notes for TechRepublic, this is why it’s highly important to “interview the people who are going to both use and benefit from analytical tools.” Getting input from stakeholders like executives, IT specialists and more before the comparison process begins helps set a baseline for how analytics are currently used and how they could be improved by bringing on new solutions.
Once decision-makers have firmed up the needs of users, it’s easier to judge platforms based on how well their capabilities line up.
How Many Users Need Access — and Is It Scalable?
Another key consideration is how many people inside and outside the organization will need access. Evaluate the scalability of any potential solutions, as it’s important to make sure the tool you choose can handle your growing data volume and user base. Consider not just your current user base and amount of data, but where your enterprise expects to be in six months, a year and more. When you’re evaluating the price of various options, be sure to note whether there will be any extra fees to add users down the line, too.
Can a Solution Integrate All Our Data Sources?
Another key criterion on which to appraise data analytics is how adept it will be at integrating data sources. As TechTarget notes, data analytics systems typically “rely on a growing number of internal and external data sources containing both structured and unstructured data.”
This means evaluating solutions in terms of interoperability with existing tools, ability to work with unstructured data and connectivity to architectures.
Evaluating data analytics offerings is a process with many moving parts, but knowing some of the key questions to ask can help stakeholders understand what they’re looking for and work toward finding the right solution.
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