Data discovery has become a crucial aspect of modern businesses as they strive to make sense of the massive amounts of data generated every day.
Let’s see what this data discovery is all about and how it is done.
What is data discovery?
Data discovery is the process of identifying, exploring, and understanding data within an organization to uncover insights and drive business value.
It involves gathering and analyzing data from numerous sources using methods like data visualization, machine learning, and statistical analysis to find patterns and relationships in the data.
Business users frequently carry out this process which can be facilitated by tools and technologies that offer a user-friendly interface for working with data.
Importance of data discovery
Data discovery is a crucial aspect of business intelligence, as it helps organizations make informed decisions based on the insights obtained from their data.
It helps to uncover hidden relationships in the data, which provides valuable information that can drive business growth and success.
By leveraging the insights obtained from the discovery process, Organizations can literally gain a competitive advantage by making smart decisions, predicting trends, and staying ahead of the curve.
Data discovery process
This process typically involves the following three steps:
This is the first step in the data discovery process, which involves collecting, cleaning, and transforming data from various sources into a usable format.
In this step, the data is transformed into graphical representations like charts and graphs to identify patterns between the data.
This is where the insights from the data are generated. Data analysts use tools such as statistical modeling, ML algorithms, and predictive analytics to identify trends and patterns in the data.
The whole process can be iterative, and it is essential to repeat the steps several times to make sure that all relevant data is included and to refine the results continuously.
Use Cases of data discovery
Data discovery can be used for a variety of things, from simplifying consumer experiences to enhancing back-end corporate processes.
The use cases will indeed increase as companies discover new opportunities from their studies because statistical and ML algorithms now make it possible for more complicated and demanding data discovery exercises.
Let’s examine some of the more popular data discovery use cases in more detail.
#1. Customer Analysis
In retail, finance, and other customer-focused industries, data discovery can be used to understand customer behavior and demographics. This can help organizations personalize their customer experience and make informed decisions about their marketing and sales strategies.
#2. Fraud Detection
data discovery can also be used in the financial industry to detect fraudulent activity by identifying patterns in transactions that deviate from typical behavior.
#3. supply chain analysis
It can be utilized to streamline and increase the effectiveness of supply chain procedures in the manufacturing and logistics sectors. To find the potential areas for improvement, the discovery process may include examining data on supplier performance, delivery schedules, and inventory status.
#4. Healthcare Analytics
Data discovery in the healthcare sector can help to enhance patient outcomes and lower medical expenses.
Factors to look for in a data discovery tool
When choosing a data discovery tool, it’s important to consider the following features:
The tool should have a user-friendly interface that makes it easy for business users to explore and analyze data without needing technical expertise.
potential to integrate with a wide range of data sources, including databases, spreadsheets, and more.
The application should be able to manage enormous amounts of data and scale to meet the organization’s expanding needs.
The tool must be equipped with powerful data visualization capabilities, including the ability to create interactive charts, graphs, and dashboards that can be used to explore and understand data.
Machine learning capabilities
The tool should have built-in machine learning capabilities such as predictive analytics and recommendation engines to help organizations uncover insights and patterns in their data.
Users should be able to share insights, evaluations, and infographics with other team members using the application, which should encourage collaboration.
Security and privacy
Must be able to protect sensitive data and comply with privacy regulations, such as GDPR.
Support and documentation
A complete set of instructions, training materials, and technical support should be provided with the tool.
The tool’s price should match the organization’s needs and budget.
Considering all these factors, we’ve summed up a list of the best tools for performing data discovery.
ManageEngine Endpoint DLP (Data Loss Prevention) is a software solution designed to help organizations protect sensitive data from theft, accidental loss, or unauthorized access.
It offers real-time monitoring and security for endpoint devices like laptops, desktops, and servers. Also, it can assist businesses in preventing data breaches and complying with regulations like HIPAA and GDPR.
It provides data discovery capabilities that enable organizations to identify and protect sensitive information such as personally identifiable information (PII), financial information, and confidential business data.
This tool scans endpoints for sensitive data and classifies it based on pre-defined policies.
Tableau is a data visualization and business intelligence software for exploring, analyzing, and presenting data.
With its advanced drag-and-drop interface and variety of visualization options, Tableau makes it easy for businesses of all sizes to turn their data into actionable insights.
This tool supports a wide range of chart types, including bar charts, line charts & pie charts, and provides advanced analytics features such as forecasting and statistical modeling.
Tableau also offers a range of collaboration features that makes it easy for teams to share data and insights across the organization.
Users can publish their dashboards to Tableau Server or Tableau Online, where others can access and interact with the data and provide. Additionally, Tableau provides mobile apps for iOS and Android.
Osano is another excellent software company that provides privacy management and data protection solutions for organizations.
Osano’s solutions include a privacy management platform that provides a central hub for organizations to manage their privacy policies, cookies, and data protection obligations.
The data discovery feature in Osano allows organizations to identify and classify personal data stored in various systems, including databases and cloud applications.
This platform also provides a data inventory that can be used to track and manage personal data over time and tools that can be used to detect & flag sensitive data automatically.
Qlik Sense is a data visualization and business intelligence platform developed by Qlik, a software company. The platform provides a range of data visualization and analysis tools that allow organizations to turn data into actionable insights.
It provides a self-service data discovery environment that allows business users to create and explore interactive data visualizations, dashboards, and reports.
The platform uses a proprietary data engine that indexes data in real-time which provides fast and flexible access to data from a wide range of sources.
Informatica is a trustworthy provider of data management and integration solutions that assist businesses in maximizing the value of their data. Its data catalog tool helps to discover and manage data assets of any company size.
Businesses can quickly scan & index metadata, profile data, and access detailed lineage information about tens of millions of data sets.
Similar to other tools, it also offers an intuitive interface to search for and discover data assets and provides contextual insights to help businesses make data-driven decisions.
In the modern digital world, organizations that effectively leverage data discovery are better equipped to deliver a greater customer experience, remain competitive, and achieve their business goals.
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Hey there, my name is Ashlin, and I’m a senior technical writer. I’ve been in the game for a while now, and I specialize in writing about all sorts of cool technology topics like Linux, Networking, Security, Dev Tools, Data Analytics, and Cloud… read more