5 Common Challenges Of Analytics Reporting

5 Common Challenges Of Analytics Reporting

What Are The Most Common Challenges Of Analytics Reporting?

contributed by Catherine Wilson

The benefits of analytics are obvious and do not need to be stated yet again.

Companies of all sizes and across industries realize that this tool is both a huge asset and a competitive necessity. But what does deserve much focus is how hard it is to implement and optimize an analytics initiative successfully.

Companies are eager to start relying on data-driven insights. But once they go searching for them, it’s quickly apparent how elusive they are and how complex it is to find them. Despite the promise of analytics reporting, many products turn out to be expensive goose chases.

The first step to avoid repeating that fate is to understand what kinds of challenges are commonly experienced. That way, plans can be developed and resources put in place before their absence becomes a crisis.

Here are 5 issues to focus on.

5 Common Challenges Of Analytics Reporting

1. Storing Vast Amounts of Data

The value of analytics is directly proportional to the volume of data the analysis is based on. Unfortunately, even with new technologies like Hadoop or cloud storage, storing large and growing pools of data is an expensive and complex proposition.

It is easy to outgrow storage capabilities faster than anyone expected. And the construction of storage systems requires careful consideration. Worst of all, storage errors lead to huge data losses, compromising the value of all analytics moving forward.

2. Staffing twith Data Experts

The best tools for analytics reporting make the process easy and intuitive. Unfortunately, many fall short of this standard. That is why companies are furiously recruiting data analysts in large numbers.

These professionals have the expertise most companies need to turn data into insights. Since, however, the demand is much larger than the supply, many companies are switching to platforms and services that can answer their ad hoc questions.

3. Securing Large and Sensitive Data Sets

Big data creates big risks and big opportunities. If data has value to a company that likely means it has value to someone else. And when huge volumes of it are stored in one location it becomes an appealing target for anyone planning a data breach or a ransomware attack.

Large scale breaches at Equifax, Yahoo and others only underscore the risk. In the rush to implement a massive data initiative it can be easy to overlook or dismiss serious security concerns.

4. Integrating Various Data Silos

Data is more valuable when it incorporates the largest number of data sets possible. Unfortunately, integrating them is often complicated and produces uncertain results. When companies are harvesting data from disparate departments as well external sources it’s difficult to confirm that every data source is accurate, complete, or up to date.

Companies go about analytics reporting believing they have all the information available. Instead they are basing insights off a limited understanding of the truth.

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5. Locating Actionable Insights

Even when an analytics initiative goes exactly as planned it’s not always an overwhelming success. The right experts armed with the right tools still struggle to find insights inside huge repositories of data.

And even when trends and patterns do emerge, it is difficult for decision makers to feel fully confident acting on them. In practice, many of these initiative fail to deliver a healthy ROI and produce more strategic confusion than anyone expected.

What is important to remember is that just because analytics reporting is challenging does not mean it’s worthless. In fact, with the right approach it’s worth a lot. But companies cannot expect to succeed without the right resources in place, resources specifically designed to mitigate challenges.

The answer? Look for solutions that make analytics reporting easy and accessible for both the end user and the IT manager.