How to Make Data Intelligence from Analytics a Reality

How to improve data intelligence and empower stakeholders throughout the organization to make faster, smarter decisions.


To compete in today’s data-driven world, organizations need the ability to discover, understand, govern and socialize their data for actionable insights. While this may seem like common sense, the truth is that some organizations don’t know how to achieve such data intelligence and are consequently missing out on valuable opportunities to make themselves more competitive. Data intelligence can help enterprises to understand what data they have, including knowledge about where relevant data is located, where it originated, how it has transformed over time, and what it means within a business context.

Without data intelligence, data is simply data. And although having democratized data insights is not a new concept, many still struggle to achieve the reality. Following are points that organizations should keep in mind to increase their data intelligence and thus empower stakeholders from every rank to make faster, smarter decisions.

Understanding Data Operations

DataOps has been around for several years but is still an evolving concept. For example, a recent survey found that, while 42% of organizations have some mix of manual and automated processes, 93% say there’s room to incorporate more automation into their data operations. When done right, DataOps can pinpoint concerns for data analytics teams and improve overall collaboration. This is important, as often, data becomes siloed where enterprises have as many data pipelines as they do data analysts, scientists, and applications — all of these need individual data sets and access rights to produce content.

Having a proper DataOps strategy in place correlates to better data intelligence in an organization by breaking down silos and enabling better business operations agility. Data intelligence helps identify “dark data,” data that is unused, which is especially helpful when data is spread across different environments. It also enables organizations to put “data first” to be more competitive, own more market share, and increase growth. This supports data democratization, capturing of real-time data needed for automated applications powering edge devices and enterprise systems. However, Data Operations is more than “DataOps” and a subset of DevOps.

Data Operations takes into account the broader view of the data pipeline, which must include the hybrid infrastructure where data resides and the operational needs of data availability, integrity and performance to maximize its potential. If the comprehension of this isn’t there, then truly beneficial Data Operations can’t be realized and improving organizational data intelligence will be difficult to achieve.

Driving Better Business Outcomes

When data intelligence is in place, it’s easier to minimize risks and liabilities in data governance. It ensures that organizations can trust that their data is right and used in compliance with regulations (GDPR, CCPA, HIPAA, etc.). Avoiding fines and penalties, aside from helping to avoid data breaches by meeting compliance requirements, also enhances productivity.

Data intelligence is the basis for sound yet agile decision-making, enabling faster insights with data integrity and resiliency while leveraging automation to shorten cycle times and reduce human error. Accelerating how data intelligence can be used, and where, enables organizations to realize data as a business advantage. In fact, 84% of organizations believe their data represents the best opportunity for gaining a competitive advantage during the next 12 to 24 months.

If understanding Data Operations helps to improve intelligence around data within an organization, then naturally smart companies will embrace and grow their data governance processes to get ahead in the market and further the value of their data. There are those who tend to think data governance is a growth inhibitor when in reality, governance ensures trust and reliability of data to better-derived value.

The biggest consideration here is trust: trust in the available data and the people who have access to it and why. More visibility and standardization of who has access to what data, when and for how long whether on-premises or across clouds can be captured with central data governance.

When data is democratized across an organization, with the appropriate security and governance, enterprises empower both producers and consumers with data intelligence to drive the right strategic decisions. Having accurate, real-time, high-quality data insights is even more important because of today’s remote workforce, in addition to the fact more data security and privacy regulators are enacted.  With data intelligence, data operations, protection and governance are aligned and strengthened because the silos between them are reduced, with teams in the front and back office empowered to work together more effectively and efficiently.


John Pocknell is a senior solutions product marketing manager at Quest Software. Quest helps customers solve their next IT challenge, from maximizing the value of their data, to Active Directory and Office 365 management, and cybersecurity resilience. Around the globe, more than 130,000 companies and 95% of the Fortune 500 count on Quest to become data empowered, deliver proactive management and monitoring for the next enterprise initiative, find the next solution for complex Microsoft challenges, and stay ahead of the next threat.