Data Quality in the Age of Data Democratization and Data Literacy
Two trending topics in data today are data democratization and data literacy. Here, we’ll explore what these two trends mean, why they are important now, and why they are likely to continue to be important for the foreseeable future.
What Is Data Democratization?
Data democracy means, in essence, that all stakeholders in an organization can access corporate data. But, true data democratization goes beyond simply providing access to data. It includes enabling everyone in an organization to leverage that data for analysis, insights, and better decision-making. Data democratization is about making it possible for non-technical business users to leverage data as needed on a self-service basis, independent of IT involvement.
The net result is that data democratization breaks down silos and eliminates the “gatekeeping” mentality that prevails in many organizations. When a broader base of business users can access corporate data assets, that increases transparency and can improve business results.
At the same time, it’s critically important that privacy and security be maintained at all times. That includes compliance with Europe’s General Data Protection Regulation (GDPR) and similar laws around the world. It requires that sensitive or confidential information be safeguarded from unauthorized users, including both external threats and internal actors.
These seemingly conflicting objectives of increasing access to data while ensuring privacy and security require a delicate balancing act. That, in turn, calls for a careful and highly intentional data governance program.
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How Data Literacy Fits into the Picture
According to Gartner, data literacy is “the ability to understand, share common knowledge of, and have meaningful conversations about having a data-driven culture.” Data democratization without data literacy is useless. Without data literacy, broad-based access to corporate information can sometimes do more harm than good. When users throughout the organization have access to powerful tools to manipulate and analyze large data sets, it is imperative that they understand what they are doing. That may include knowing about potential pitfalls or limitations. An effective data governance program can help to mitigate potential issues by making information available in contexts and formats that can be better understood by everyday users.
Data literacy also implies the ability to ask compelling questions and to understand how the organization’s data assets (including externally sourced data) may be put to use in finding answers to those questions. Again, a good data governance program can be extraordinarily valuable insofar as it helps to organize and catalog data assets so that they are visible to the people who need them.
The Vital Role of Data Quality
Data quality is taking on greater importance as this broader trend toward greater data democratization and data literacy continues to unfold. Consider what happens when organizations increase their focus on data-driven analysis and insights. There are enormous potential benefits whenever we see a shift from “seat-of-the-pants” or “back of the napkin” thinking to decisions that are well-grounded in real-world data.
As data drives decisions with potentially greater consequences than ever before, the trustworthiness of that data is absolutely essential. Data quality is just one of the pillars of data integrity. The others are integration, data enrichment, location intelligence, and data governance. Without all five, it is impossible to optimize the value of the data assets within your organization.
A strong data quality program ensures that information is consistent across multiple data stores and that it is complete, accurate, and accessible by the people who need it in a timely manner.
Powerful tools such as predictive analytics are being used to develop insights that inform key business decisions. Although data-driven decisions have the potential to be highly impactful, errors and omissions can likewise be highly impactful. If you are embarking on a short journey, small variances in your direction will have a relatively minor impact. If, on the other hand, you intend to travel a great distance, then even a minor deviation in your compass heading can lead you quite far from where you intended to be.
For this reason, data quality is simply a non-negotiable requirement for organizations that intend to use information to their advantage. Together with the other four pillars of data integrity, it ensures that the data being used to drive important business decisions is trustworthy and that users throughout your organization will have confidence in the insights that emerge from it.
As the global leader in data integrity, Precisely provides a fully integrated suite of products that helps enterprises to build and maintain a foundation from which to generate meaningful insights to support confident business decisions. To learn more about how you can strengthen your data governance framework with improved data quality, read Precisely’s free ebook Fueling Enterprise Data Governance with Data Quality today.