The science of evaluating raw data, or what we call data analytics, is a complex field with its own unique language. The process can be pretty complex and hard to grasp. That’s why business leaders aren’t always aware of how crucial data analytics services are to ensure the success of their organization.
As a result of this obscurity, the field of data analytics has spawned many myths and misconceptions that have filtered into the public consciousness. Let’s break down all these myths that could possibly have an adverse impact on your business.
Myth #1: Data Analytics Leads to New Discoveries
In theory, data analytics enables the discovery of new and useful information. Those pieces of information are crucial to decision-making. That much is true, but to claim that analytics will automatically lead to new discoveries is nothing but a misconception. The information you get all depends on the data gathered. If the data itself did not contain new pieces of information, then no discoveries shall arise from the analytics.
Myth #2: Data Analytics Is Too Expensive
This is a common misconception that has circulated for many years, preventing companies from utilizing data analytics to their benefit. The truth is, not all data analytics endeavors require a significant investment. A data analytics solution can be quite tangible and cost-efficient, depending on the type of solution. You can even gain something from it. If you’re looking for a tangible benefit, data analytics enable companies to make better-informed decisions, in turn maximizing the ROI.
Myth #3: Data Analytics Is Too Time-Intensive
Many business leaders who veer away from data analytics services do so because of the belief that the process is too time-intensive. In truth, this all depends on the data provided. If the data solution isn’t a good fit, then it’s infinitely harder to process and analyze. Look for solutions that integrate with existing channels, provide a full view of activities driving revenue and offer execution services. Doing this can make analytics go a lot faster, even allowing it to be done in a few clicks!
Myth #4: Data Analytics Algorithms Are Never Wrong
Most people are under the impression that algorithms are these super programs that are fail-safe and that the results they produce are all you ever need to make a decision. While it is true that most algorithms are locked down following rigorous testing, it can be potentially disastrous to trust them implicitly.
Stakeholders must always question the developers to understand how the algorithms arrived at those answers. This will help maintain transparency in the process and allow human agents to have the capability to verify the results if needed.
Myth #5: In Data Analytics, All Data Is Created Equal
There is no such thing as data that’s “good enough.” This view completely ignores data quality and strategy. If you have a large organization, you probably receive and gather terabytes of data every minute. The question is, “what is worth your time to analyze?” That’s the strategy question. Next is exploring the quality of the data you have and determining which is usable and which isn’t relevant to what you’re analyzing. Of the millions of terabytes of data you collect, expect that many of them will not be used by analysts, depending on the kind of solution you’re looking for.
Conclusion
The rapid growth and success of data analytics as a viable decision-making tool for businesses has produced a number of misconceptions that many people cling to. Those myths listed should be explored and understood so you could avoid falling into their trap.
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