What is Data Discovery? The Ultimate Guide

Table of Contents

    Technologies we rely on for day-to-day operations generate vast amounts of data at an unprecedented rate, from customer interactions to supplier lead times, or financial activities: the list goes on. With so much data at your disposal, it’s best to put it to good use so it benefits you and your organization.

    Nonetheless, such data is usually siloed and often remains fragmented across various systems, limiting its utility. This abundance of information can’t be helpful until you consolidate it into one platform and uncover patterns. That’s precisely what data discovery is all about, so let’s dive in!

    What is Data Discovery?

    Data discovery refers to the process of exploring, analyzing, and visualizing data to uncover outliers, patterns, and trends that may not be immediately apparent – informing decision-making.

    Data discovery concept; close up of a human eye with numbers and data in background
    Discovering Insights

    In other words, data discovery empowers you to gain valuable insights and make data-driven decisions to power innovation, enhance efficiency, and improve business performance.

    What Does the Data Discovery Process Entail?

    Data discovery involves navigating your data warehouse and applying advanced analytics to examine data structures, transform complex data, and apply visualization techniques to identify valuable information – that would have otherwise remained unknown. It’s akin to when a soccer player steps back from the ball to assess the goalkeeper’s stance before taking a decisive penalty kick.

    In the same way, data discovery allows your organization to momentarily detach itself from individual data points and combine data on one platform to see the big picture. In turn, this drives your business strategy and overall decision-making. So how does it work and which steps does it involve?

    The Data Discovery Process: How is Data Discovered?

    Data discovery generally has three core steps. Understanding each of the steps provides an idea of how data discovery works.

    1. Define Scope & Objectives

    Your first step is to clearly outline the goals and objectives of the data discovery process, including project timeframes, data sources you’ll be using, and desired outcomes you want to achieve.

    You can start by answering these questions:

    • What’s the business objective we’re trying to achieve by implementing a data discovery process?

    → Are you trying to understand customer churn rates? Identify factors influencing sales performance? Improve operational efficiency?

    • What are the constraints or limitations of the data discovery process?

    → Are there specific data privacy regulations we need to comply with? Do we have access to all relevant data sources, or are there gaps in the available data?

    That way, you ensure your data discovery process is focused, aligned with business priorities, and ultimately delivers actionable insights that drive tangible value.

    2. Gather & Collect Data

    Once you’ve got a clear goal, it’s time to unify all your data from various sources, including databases, spreadsheets, CRM systems, web analytics tools, social media platforms, APIs, or any other repositories where relevant data resides to create a single source of truth.

    This step is often the most challenging: between accessing data, connecting systems that aren’t made to talk to each other, or handling large data volumes, all while ensuring data security and compliance.

    blog en data integration all connectors
    Pull data from your favorite sources!

    3. Get Ready For Data Preparation

    Now that you’ve connected all your data sources, you need to get your data ready for analysis – or prepare it. This stage includes all pre-processing tasks such as data cleaning, transformation, and calculation.

    Easily Clean, Transform, and Enhance Data with Data Flow Module

    The objective is to ensure high-quality data by identifying errors, missing values, duplicates, and inconsistencies in your datasets. But also perform transformation tasks to deliver standardized, normalized, and reliable data for effective analysis.

    4. Analyze Data with Advanced Analytical Techniques

    Now’s the time to dive into the analysis and explore it with Data Analytics. This process involves applying appropriate analytical techniques, such as statistical analysis, machine learning, or data mining, to uncover patterns, correlations, and insights within the data.

    5. Visualize and Communicate Insights

    Once, you have the results of your analysis, it’s time to interpret and present your findings in a clear, intuitive manner, making it easier to communicate insights and facilitate decision-making.

    For this, utilize data visualization techniques such as bar charts, line graphs, scatter plots, heatmaps, histograms, or pie charts based on the insights you want to convey.

    dashboard reports template

    Whether you’re building custom dashboards or pixel-perfect reports, tailor your visualization to the intended audience and tie back to the objectives of your analysis. Remember, you’re the one telling the story hidden with the data.

    Insights have more impact shared, so automate your dashboard and report publication so your teams, clients, or stakeholders can easily act upon your data-driven insights.

    6. Iterate & Repeat

    The dynamism of industries necessitates the repeatition of the data discovery process to stay updated with current trends and continually derive new insights – hence leading us back to step one: Preparation.

    Continously iterate on the analysis as needed, refining approaches, exploring additional variables or data sources, and validating findings to ensure robustness and accuracy.

    Data discovery is an iterative process that can seem – and often is – tedious yet benefits far outweigh the time and effort required to achieve it, so let’s explore some benefits of data discovery.

    What are the Business Advantages of Data Discovery?

    Every industry faces unique challenges in today’s rapidly digitalizing world, and data discovery is a key aspect of business agility. By providing a comprehensive view of your company’s operations, data discovery makes it easier to understand and address the challenges your organization faces:

    Anticipate Problems Before They Hamper Operations

    Your business can only thrive if you anticipate problems and address them before they hinder operations. Data discovery is key to detect market trends that are still imperceptible and prepare for them accordingly.

    Some of the problems you can anticipate and mitigate include:

    • Sudden interest in a specific product and placing more orders with your suppliers before competitors’ orders lead to a shortfall and price hikes.
    • Loss of customers due to a market campaign that doesn’t resonate well with them. In this case, data discovery will help you determine how many customers you’ve lost and where they could be heading. With such insights, it’s easier to avert further hemorrhage.
    • Faulty products with high return rates contribute to negative reviews on your website. Through data discovery, you’ll access the underlying problem and determine ways to keep selling the products or return the entire inventory to the supplier.

    Improved Understanding of Your Customers

    Your business can only meet its goals if you understand your target market fully. Knowing your customers helps you plan for the future. Data discovery provides a 360-degree view of your customers. By helping with day-to-day reporting, it allows you to discover future trends.

    Through data discovery, you’ll establish whether your customers or products are as profitable as it seem and those that could be denting your bottom line. When you gain daily insights into your customer base and product line, it will be easier to predict the future and plan for it accordingly.

    Enhanced Customer Experience

    The most significant challenge businesses face is maintaining quality customer service. Data discovery helps you understand and fulfill customer needs. On average, consumers spend nearly $1 million per minute online. Thus, understanding the customer journey helps you predict their buying behavior and the products they might consider after the initial purchase.

    Through data discovery, you tap into a rich record of customers’ buying behavior and preferences. It can also help you to minimize buying friction and leverage affinity marketing to band similar groups of buyers according to their shared needs and preferences.

    By understanding customer preferences and predicting what they may want to buy in the future, data discovery helps you serve their needs and enhance them. Likewise, it enhances the alignment with your customers for greater satisfaction.

    Identify Upselling and Cross-selling Opportunities

    Since data discovery entails combining data from multiple sources into one platform, it allows you to pinpoint upselling and cross-selling opportunities that were hitherto hidden from view. Data discovery makes it easy for you to quickly analyze customer data and predict what they might purchase next. It could be additional products (cross-sell) or premium versions of what they currently use.

    Getting more from the data you collect and store is the most critical component of your organization’s upselling and cross-selling efforts. Data discovery allows you to deeply analyze your customers’ data and gain more insights into it. From these insights, you can identify opportunities for raising more revenue from your customers by offering more relevant products. In the long run, you’ll increase customer value and benefit the business and its customers.

    Enriched Data Quality

    As the volume of data in your ecosystem grows, so does the need to maintain its quality. An organization that deploys data discovery tools can easily maintain data consistency and quality. Data quality encompasses your data assets’ completeness, accuracy, and consistency. Nevertheless, it’s hard to imagine how you can embark on the journey toward data quality without having a clear picture of your data ecosystem.

    Since most organizations grapple with many information systems, maintaining data quality is challenging. According to the principles of data quality, your data systems must be in sync and consistent for quality to be maintained. Disparate systems should get reconciled, especially if they touch on common information, including customer data.

    Data discovery provides a sure-fire way to catalog and profile your organization’s data and guarantee its consistency and quality. It also provides greater visibility into your data decay. For instance, CRM databases tend to suffer from rapid data decay. This can only be averted if you implement a proactive data quality program. Data discovery is the first step toward realizing your data quality dream.

    Compliance With Regulatory Requirements

    Consistent data discovery and cataloging go a long way in enabling compliance with increasingly complex regulations. In recent years, there has been an uptick in the number of regulations designed to protect the privacy and security of personal information. Your organization must comply with multiple regulations, from The California Consumer Privacy Act (CCPA) to the General Data Protection Regulation (GDPR).

    image showing the comparaison between ccpa and gdpr

    If you operate in a regulated industry such as banking or healthcare, you must comply with many other stringent data security regulations (such as HIPPA). Violations can result in hefty financial penalties, not to mention the negative word-of-mouth that comes with it. However, that can be a tall order for organizations with siloed data.

    Data discovery allows you to understand the data you collect, its sources, its storage and transmission, and the security measures in place. It becomes easier to spot outliers and potential threats to manage data and improve risk management proactively. Ultimately, it enables you to stay compliant in an increasingly complex regulatory environment.

    → Unlike other similar processes, data discovery does not necessitate building elaborate models. Instead, companies use data discovery as a component of their business intelligence software to get a clear picture of their data ecosystem in a visual format (with charts, graphs, or maps). With businesses collecting more complex data by the day, it’s best to invest in a data discovery tool that allows you to connect, automate, prepare, and visualize your data promptly and conclusively.

    What Data Discovery Tool Should You Use?

    Your organization exists in an era of digital transformation, and you can only succeed if you know how to leverage the data you collect. Data discovery is only as effective as the tool you use. You need a tool that helps you learn more about the data at your disposal and act on the insights accordingly.

    ClicData is the data integration tool you need to combine and extract data from various sources and understand your data ecosystem better. The interactive and visual business intelligence solution allows you to cross-filter different attributes on one dashboard and understand previously unknown relationships. With this tool, you’ll make smarter, data-driven decisions that help you usurp the competition. Sign up to start your free trial.