Be Data-Driven, Not Gut-Driven

Every day, companies rely on data to make critical choices, yet the quality of their data analytics varies greatly. Few firms have the bandwidth or experience to sort through millions of data points in many forms and from diverse sources to reveal all the value hidden inside unless they have an in-house data science team. Data discovery enables businesses to turn all of this data into actionable information.

What is Data Discovery

The process of finding, cataloging, and classifying data in various systems is known as data discovery.

The purpose of data discovery is to figure out what kind of data is being saved and processed so that the company can get something useful out of it.

Data discovery is critical for understanding and detecting all data processing activities when it comes to compliance and personal data processing.

Benefits of Data Discovery

Business intelligence is a subset of data discovery. It is the process of combining data from numerous databases into a single source so that trends may be investigated and detected more easily. The five advantages of data discovery for firms today are listed below:

1. A complete picture of company data: Data discovery gives businesses a big-picture view of their multiple data sources, allowing them to combine them in their studies and come up with well-rounded answers to their difficulties or client needs. A retail bank, for example, can aggregate client data from its website, mobile app, social media platforms, and ATMs to get a more accurate picture of each person it serves and better understands their behavior.

2. Automatic data classification based on context: Every day, businesses acquire more data from more sources and in different formats. Data discovery enables proper classification of all of this data depending on the channel, conditions, and context in which it was acquired. Retailers, for example, can distinguish between customer data acquired by their marketing, sales, and service teams in order to evaluate their overall customer experience rather than a single point in time.

3. Improved risk management and compliance: Risk management and compliance have risen to the top of company agendas as data quantities have grown and governments have increased their investment in data security. Data discovery assists firms in identifying outliers and potential dangers in their data so that they may better handle them. Companies can also put their data management methods to the test to ensure that they comply with legislation such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR).

4. Democratized insight and decision-making: To acquire business insight, IT and data skills should not be required. Data discovery simplifies data analysis for all stakeholders in the organization, regardless of their data literacy. Sales teams, for example, can see how their strategies drive or stop leads throughout the sales funnel, finance teams can spot and trim excess fat from their organization's operating expenses, and marketers can connect data from multiple customer touchpoints to see how their activities align with sales success. In short, data discovery offers an almost infinite number of applications to meet the needs of various business teams.

5. Real-time data controls: Companies can take precise actions to the data they acquire in real-time using predetermined controls or contextual variables, ensuring that it is appropriately kept and analyzed, and that data practices are secure and compliant. The discovery of data is critical to achieving this level of control.

Steps of Data Discovery

1.      Preparation of data

2.      Visual evaluation

3.      Advanced analytics & future prediction

Mistakes to Avoid in Data Discovery

1. Poor Quality Data:

The quality of data visualization tools is only as good as the data that is entered. If a company doesn't have an enterprise-wide data governance strategy in place, it's possible that its charts and dashboards are based on faulty or missing data. The danger of a data breach can be reduced by implementing an enterprise-wide data governance policy.

2. Rogue Dashboards:

Every dashboard begs the question: Is the data correct? Is the approach of analysis correct? Most importantly, can this data be used to make vital business decisions?

This is the "Wild West" of data visualization, with rogue dashboards infiltrating the organization in an unregulated and disconnected manner. Users alter data and fields with no audit trail and no way of knowing who did what. This divergence can lead to erroneous information and poor decisions, as well as increased administrative costs and the emergence of many versions of the truth.

3. Advanced Analytics Limitations:

Data visualization isn't as common as standard BI techniques. However, as technology advances, this enhanced business intelligence functionality will become more in demand. Users, for example, demand the opportunity to integrate unstructured data from social media or use predictive analytics to make better decisions. As a result, firms must choose a data discovery tool that is supported by a BI platform if they want to extend their business intelligence capabilities to meet future data discovery and visualization needs.

Conclusion:

To sum up we can say that Data Discovery is one of the most important activities and an integral part of business operations. It can’t be separated from the management. A good and efficient data discovery must result in benefits to the organization and there is no doubt in that. And avoiding data discovery is not a good decision at all.