How to Speed Up Data Reporting

Reading Time: 3 minutes

The modern company’s relationship to data is constantly evolving over time. Whereas data used to be a byproduct of doing business, now it is an actual commodity—one organizations can’t afford to do without. Companies who can monetize their stored data unlock the benefits of tapping into previously hidden revenue streams and streamlining their internal operations. As TWDI notes, monetizing data “requires you to think about data as a strategic asset in new ways.” And the only way to do this is by engaging in better analytics.

One past pitfall of business intelligence (BI) reporting was the delay between requesting a report and its completion, sometimes weeks or months. In other words, there have historically been hurdles between valuable company data and the actual end users who need it. But the latest BI tools are breaking down these barriers, reducing the time it takes to put company data to good use. Current tools can accomplish the same tasks in seconds or minutes.

Wondering how to speed up data reporting? Consider these strategies.


The Problem with Siloed Data

Siloed data stands between end users and speedier data reports. These isolated data sources drive up costs and slow down analytics as companies move to monetize data. There are a number of reasons companies may experience data silos:

  • Disparate systems
  • Proprietary security controls
  • Rapid growth with supportive infrastructure
  • Vendor compatibility

To combat the inconvenience and expense associated with data silos, companies must focus on integrating structured data into one usable system. The goal is to avoid a system of silos, so you can gain the competitive advantage of giving business users access to all kinds of data. This, in turn, drives better business decisions because employees and partners no longer must work around “blind spots” in their data accessibility.

Furthermore, a truly integrated solution allows for more timely outcomes because its algorithms will be capable of pulling data from multiple sources.


Implement Self-Service Analytics

Put simply, self-service analytics allow end users across an organization to access company data. The result? Here’s how Analytics India Magazine describes it: “These same workers should also have the ability to analyze and discover insights about their data without assistance from the elite few — the data scientists and IT developers.”

So, self-service data analytics aim to eliminate gatekeepers to data by making it accessible to all. This includes even those business users without explicit training in back-end logistics related to data. This phenomenon is known as data democratization because it empowers everyone to ask questions and seek answers from data rather than imposing a hierarchy of access.

Search-Driven Analytics in Action

Here’s an example: Say a marketing manager wants to generate a report about customer behavior to inform an upcoming campaign. Access to a relational search engine will allow this employee to query data directly rather than having to submit a request to a centralized IT team. The results will come back immediately in the form of a best-fit chart, although the marketing manager can tweak the appearance and format as needed. Then they can click to share their findings with relevant colleagues like fellow marketers, sales leads, executives and more.

Advantages of Faster Data Reporting

The primary advantage of speeding up data reporting processes is that companies can make confident, data-driven decisions faster. This includes identifying new opportunities for revenue and improving current operations to optimize for efficiency. Plus, individual users end up sinking less time and effort into producing data reports. This frees them up to focus on other important tasks. IT and data specialists can focus more on organizing and maintaining data infrastructure rather than producing reports.

Utilizing the latest tools available is the first step in successfully speeding up data reporting.

All opinions expressed on USDR are those of the author and not necessarily those of US Daily Review.
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