What is data discovery and why does it matter?

Data discovery involves collecting and analysing data from various sources and is often used to identify trends, relationships or outliers between various data items. This process can be actioned from a single database or across multiple disparate data processing systems, allowing organisations to turn relevant data into actionable insights and make informed decisions.

The Data Discovery Process

Data discovery enables you to get the full picture and from identifying outlier data to analysing trends and spotting dependencies between data items, the process of data discovery can be boiled down into four key components:

1. Data collection
2. Data cleaning 
3. Data analysis
4. Data communication and visualisation

Smart data discovery helps your business or organisation to maintain high data quality levels across the organisation and enabling the right people to have the right data at the right time.

Data Collection: collating the data you have

The first step in the data discovery process is to gather all relevant information from various sources such as databases, websites, applications and reports. No single data stream tells the complete story, therefore, gaining an overall picture of the available data from multiple sources enables organisations can gain a comprehensive view of the patterns and trends within their data. This is largely a manual exercise where data specialists discover data from various sources.

Data Cleaning and Data Classification: understanding data discovered

The cleaning process can include removing duplicate, inaccurate or irrelevant information that may have been collected as part of the initial data collection phase, providing a more precise direction. This is a crucial step to identify only relevant and accurate information, as any discrepancies can lead to misinterpretations or incorrect conclusions. Data cleaning also involves the identification of outliers, which are data points that lie outside the central trend of the data set and may be presented due to errors in data entry or measurement. Data discovery software can help with this part however an understanding of the data is crucial in order to make sure the cleansing and classification of data is correct.

Data Analysis: analysing data for action

The next step involves analysing and understanding any patterns or relationships in the data. This can include various mathematical metrics such as mean, median and mode to gain insight into how the numbers interact with each other and detect. Usually supported by data scientists, this phase is all about identifying and understanding patterns, using data visualisation techniques to assess the quality of the data collected, and hypotheses can be tested for further analysis.

Data Communication and Visualisation: the final piece

Another critical stage of the data discovery process is effectively communicating the findings and insights to relevant team members. This may involve presenting the data in a form that key stakeholders can quickly visualise and understand, highlighting trends, patterns or relationships that have been identified. Data communication enables organisations to make decisions based on their data, improving the accuracy of their decisions and leading to better results.

The Benefits Of Data Discovery

Data is at the heart of every organisation, but to get the most value out of available data, it’s crucial to understand the existing patterns and relationships. When you have the agility to find and interpret data insights quickly, you can make smarter and faster decisions with greater precision. Intelligent data discovery allows organisations to uncover trends and patterns that may not have been noticed, which can help improve efficiency and make informed decisions. Data discovery provides a clear picture based on accurate insights, from the shift to hybrid working and cloud-based solutions to the many users visiting your websites and applications.

Data Isn’t ‘the New Oil’ – It’s So Much More!

More businesses are treating their data like their most prized asset. The information businesses collect about their customers and operations can provide a competitive edge by uncovering new opportunities and giving them an understanding of the market. When you transform this intelligence into a competitive advantage, you can enhance customer experiences and elevate efficiency.

Automated data discovery tools and solutions- are you looking to AI for help?

Here at Data Privacy Group, the OneTrust online platform is at the core of our solution. Companies of all sizes face increasing pressure to comply with complex regulations, meaning advanced data discovery is now more critical than ever. Whether you’re looking to quickly and easily understand how your data is being used, wish to create an easy-to-comprehend, holistic view of your data items or want to eradicate manual data discovery, which can often be time-consuming and yield incorrect results, we can help you unlock the power of AI-driven Data Discovery, ensuring you have a readily accessible, visual and well-classified data landscape.

To learn more about The Data Privacy Group and how we can help you, please contact us today.