Data enables organizations to make informed decisions and better understand customer and business needs. It also allows organizations to solve business problems for operational excellence, risk management, and growth. However, for companies to leverage data, they need to visualize, analyze, and derive insights from it. Data discovery can help with that.
In this article, I’ll explain what data discovery is and go over its phases, benefits, and various use cases. Let’s begin with that definition.
What Is Data Discovery?
Data discovery begins with collecting data from multiple sources, such as data lakes, repositories, and applications. After that, you’d consolidate, classify, and catalog this data into a single repository for you to evaluate easily.
How does this help exactly? This allows you to visually evaluate the data to better understand and analyze data trends and patterns. As a result, you can derive useful business insights. Data discovery is usually associated with business intelligence (BI). It bridges the gap between the technical team working with data and the stakeholders who make decisions based on data.
Data discovery tools enable tech and non-tech users, like the stakeholders, to easily identify common patterns and trends using visual data representations. In essence, anyone with little to no tech experience can perform the data discovery process from large and heterogeneous datasets.
That said, let’s go further and look at the different phases in the data discovery process.
Data Discovery Phases
You have 3 major phases to consider—data preparation, visualization, and deriving insights through analytics. Let’s look at each one of them, starting with data preparation.
1. Data Preparation
This is the first step in data discovery. It involves generating the required dataset. You usually merge data from multiple sources like databases and data centers. Afterward, the next step is to homogenize the unstructured data into a common structure. You’ll also denoise the data to achieve consistent quality and format for downstream processing.
Data visualization is one of the most effective and powerful means of deriving data insights. It’s also an easy way to comprehend the insights and value from datasets. Visualization is also called data mapping. It displays data in visual formats such as charts, maps, and graphs. Then, you can easily pick up these formats with your brain’s pattern recognition capabilities.
3. Advanced Analytics
Finally, advanced analytics allows you to extract context-specific insights from the data. This enables you to get a complete picture of the requirements so you can easily summarize them into detailed reports. The analysis aims to describe and generate the implications of the visualization to provide descriptive statistics.
This is possible due to the preprocessed data from the data preparation phase and visual aspects generated through visualization. Advanced analytics allows you to find data-driven patterns and relationships between data entities that you can use to derive valuable insights.
Now that you have an idea of the data discovery phases, let’s take a look at the benefits of leveraging data discovery for your business.
Data Discovery Benefits
Data discovery is an industry and business-agnostic process of generating valuable insights to make better business decisions. Due to the wide-scoped techniques and processes involved in data discovery, such as data identification, segregation, analysis, visualization, and more, you have several benefits to consider:
- Provides you with better visibility of where your data resides within your organization
- Identifies and prevents the data silo formation
- Enables easy data classification and segregation
- Reduces data migration risks such as data loss, conflicts, and corruption
- Enables you to generate valuable data-driven business and operational insights
- Helps implement data protection policies across your organization
- Prevents several data-related cyberattacks, such as data theft or man-in-the-middle attacks, by helping you identify the respective sensitive data
- Improves your business’s compliance and risk-management
- Provides real-time granular control over your data
- Allows you to make customer-centric business decisions based on your data
- Helps you create a disaster recovery plan
Clearly, this process can help businesses of all shapes and sizes and is industry-agnostic. Next, I’ll discuss several data discovery use cases that can benefit your business.
Data Discovery Use Cases
Data discovery can help multiple businesses in different industries to make better data-driven decisions and explore insights. Here are some of its different use cases and applications.
Several businesses lose a good portion of their business revenue and reputation due to fraud. Fraud can include insider threats and a variety of cyberattacks, such as ransomware. The data discovery process can detect data silos and outliers. This helps you strengthen overall data security.
Data discovery can help businesses identify customer journeys and potential lead generation opportunities. It helps you map the data in a way that helps uncover potential leads and sales opportunities.
Because of the broad-scoped nature of the data discovery process, several activities performed for data discovery, such as data identification, segregation, and analysis, can help you comply with several regulations, such as GDPR.
Data discovery is also a very important business development driver, enabling your key stakeholders and business leaders to easily visualize the data to make business decisions.
Strategic planning is another important data discovery use case that can help you identify the key areas you need to focus on in your business. It can give you a contrast of all the aspects in an easy-to-understand visual format to strategically plan ahead of the competition.
Customer Issue Identification
Lastly, being able to gauge and understand customer needs and requirements is one of the most diverse and complex metrics in any business. With data discovery, you can easily identify the specific customer issues for you and your business to focus on.
You’re now equipped with the tools to implement data discovery in your business. Before you head off, let’s have a quick recap on everything discussed so far.
With businesses worldwide going digital, we’re witnessing an exponential data increase. Data is all around us, so why not use this fact?
Data discovery is a business-agnostic process of generating valuable insights to make better business decisions. You learned the 3 data discovery phases, including data preparation, visualization, and advanced analytics. You can benefit from incorporating these approaches into your business—it can help you detect cyberattacks, reduce data migration risks, and more.
Finally, you learned that data discovery has use cases across different industries to help with data-driven decisions and insights. Some data discovery use cases include lead generation, compliance, business development, strategic planning, and customer issue identification.
Do you have more questions about data discovery? Check out the FAQ and Resources sections below!
What are some top data discovery tools?
Considering the broad-scoped nature of data discovery, you have several tools at your disposal. FirstRain is a powerful tool for sales intelligence and prospecting. Other tools include Logikcull, a reliable security option, and Tibco for product analysis.
What are some data-centric cyberattacks?
Some major data-centric cyberattacks that involve either data theft, corruption, or damage include phishing, man-in-the-middle (MITM) attacks, insider threats, cyberstalking, and various malware.
What is data compliance?
Data compliance is ensuring that businesses follow the standards and guidelines needed to ensure their data is safe from theft, corruption, or misuse. As mentioned previously, data discovery can help you be data compliant, among several other benefits.
What is business intelligence?
Business intelligence, or BI for short, consists of strategies, tools, and technologies to perform data analytics, visualization, and mining to help businesses make better data-driven decisions. Data discovery is a component of BI.
What is disaster recovery?
Disaster recovery is a process that involves a set of procedures, policies, tools, and techniques to enable an organization to regain control and operational continuity after a disastrous event such as a cyberattack. Data discovery can help you and your business draft a strong disaster recovery plan.
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