What is data discovery?

Data discovery is key to turning massive amounts of information into actionable insights. It’s the process of exploring and analyzing data to identify patterns, trends and opportunities that can drive smarter decisions. It allows organizations to have a comprehensive understanding of their customers, market trends and operational performance. With this knowledge, they can identify new opportunities, optimize processes, improve customer experiences and mitigate risks.  

A modern data platform can help businesses streamline discovery and sift through complex datasets, extract what matters, and generate insights quickly. The process becomes easier when you can navigate internal and external data sources easily with the correct permissions and visibility, promoting data security and privacy. 

Today, organizations collect data from countless sources – customer interactions, transactions, social media and more. Unlocking its potential enables leaders to make informed decisions and gain a competitive edge. But to achieve this, businesses must invest in a modern data platform – a unified, cloud-native solution that enables seamless data storage, processing, sharing and analysis at scale – that empowers them to easily collect and analyze vast datasets. 

When it comes to data discovery, having high-quality data is essential. Data governance frameworks establish rules and guidelines for data collection, storage, maintenance and use, helping ensure that data is accurate, complete and consistent. It also enables the right people to get access to the relevant data at the appropriate time. 

With the increasing focus on data privacy and security, organizations must adhere to various regulations, such as the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), when considering data sharing and discovery. Data governance practices help businesses establish processes and controls to protect sensitive data, ensure data privacy and meet compliance obligations. This not only mitigates the risk of data breaches but also builds trust with customers and stakeholders.

Let's explore the benefits of data discovery with a modern data platform:

Data has become more than something to collect and analyze. It’s an asset you can easily and securely make available inside and outside your organization to streamline operations, swiftly deliver more-personalized customer experiences and open up new market opportunities. As a data provider, you can also securely monetize your data and create self-service relationships between your organization and an endless number of data consumers. To make data discovery possible, these components are often necessary: 

The first step is to identify the data sources and types available within your organization. This includes databases, files, APIs and more. By understanding the data landscape, you can determine which sources are relevant to your analysis.

Organizations inside an enterprise acquire crucial insight by analyzing data they share with each other. For example, finance teams need sales data to forecast future financial performance. Outside an organization, retailers share sales data with their vendors to manage inventory and supply chains. 

Once the relevant data sources are identified, the next step is to collect the data. This involves extracting, transforming and loading the data into a centralized location for further analysis.

Raw data often contains errors and inconsistencies. Data cleansing is the process of identifying and correcting these issues to increase accuracy and reliability of the data.

In many cases, data is spread across different sources and formats. Data integration involves combining data from various sources into a unified format, enabling a comprehensive analysis. This also involves data profiling to understand the data quality and data lineage to track the data's origin and transformation.

This step involves exploring the data to gain an initial understanding of its characteristics, patterns and relationships. It allows analysts to formulate hypotheses and identify areas of interest for further investigation.

Visualizing data through charts, graphs and interactive dashboards helps in understanding complex patterns and trends. It allows stakeholders to easily grasp insights and make data-driven decisions.

Using advanced analytics techniques, such as statistical analysis, machine learning and predictive modeling, the data is analyzed to uncover meaningful insights and patterns.

Whether you are looking to analyze customer feedback, detect trends or improve decision-making processes, you need a strategy for transforming data into actionable insights. Here’s how: 

Data discovery is more than just a series of steps; it's a mindset that values curiosity, exploration, and a commitment to continuous improvement. Embrace the spirit of discovery, and you'll find that your data becomes a strategic asset.

For an effective data discovery process, it is essential to follow these best practices: