Data discovery plays a critical role in modern analytics and business intelligence tools. Organizations that want to unlock deep insights into their data and gain market knowledge that will give them a competitive advantage need to invest in data discovery tools.
However, before fully investing in data discovery, you need to understand what it is and how it works. This post will take a closer look at this topic and explain the data discovery process.
Whether your organization is looking to improve its marketing campaigns or develop more efficient manufacturing processes, data discovery can provide the insights your business needs to succeed.
What Is Data Discovery?
Data discovery involves collecting and evaluating data from multiple sources to uncover hidden trends and patterns. The data discovery process allows business leaders to take a step back from individual data points and unlock broader trends from the combination of internal and external third-party data sources.
Leaders and key stakeholders can make better, more strategic business decisions when they can see the big picture. In addition, since data discovery almost always involves data preparation and cleaning, this process also ensures that bad data doesn’t infiltrate the analysis and distort conclusions.
Data discovery also enables business users in every part of the company to gain a valuable understanding of customer behavior, operational efficiency, and other key metrics without technical data expertise.
In recent years, Artificial Intelligence and Machine Learning algorithms have been utilized to advance the capabilities of data discovery and help organizations access complex data sets that wouldn’t be accessible through manual data discovery methods.
Breaking Down the Data Discovery Process
Data discovery is an iterative process that is refined over time. There are five critical phases of the process, which include the following steps:
- Identify organizational needs
- Data combination
- Data preparation
- Data analysis
- Record and iterate
Identify Organizational Needs
Before the data discovery process begins, it is important to define organizational goals and set a clear purpose. For example, what type of data points would be beneficial for your organization to have? What aspects of your business would you like to improve with better data?
While having a clearly defined goal is critical, your organization also must remain open to gaining unexpected insights. The most valuable insights your business derives from data discovery might be the ones it wasn’t looking for.
Data Combination
The success of the data discovery process relies on combining data from multiple sources. No one data stream will give your organization a complete picture. Therefore, your business must be willing to combine data from internal and external sources to get a comprehensive view.
Data Preparation
Once your data has been combined, it must be cleaned and prepared for analysis. Data preparation reduces distractions and bad data and helps your organization get a clear view of the combined data.
Preparation and cleansing are critical to the success of the data discovery process. If bad data is allowed to be part of your final analysis, your organization risks drawing the wrong conclusions and making bad business decisions.
Data Analysis
After data from multiple sources has been combined and cleansed, leaders can analyze the data for a complete view of their operations. The true benefit of data discovery is that it enables leaders to gain insights that otherwise would have remained hidden.
Organizations can also utilize AI and Machine Learning tools for more thorough analysis and added insight.
Record and Iterate
Data discovery is not a one-time process. Instead, data discovery is an ongoing, iterative process that continuously improves. When you’ve reached the end of the data discovery process, record the things you have learned and begin the process again.
The Benefits of Data Discovery
Data discovery has several benefits for businesses. The most important benefits to cover include the following:
- Complete overview of company data
- Greater insight
- Improved risk management
- Automatic classification
Complete Overview of Company Data
Data discovery gives organizations a macro-level view of all data streams. As a result, companies can form well-rounded solutions to their challenges. Too often, data analytics focus on one data stream, which is an incomplete picture of an organization’s operations. As a result, half measures are taken because organizations lack complete context.
Data discovery ensures that business leaders have a comprehensive overview and understanding of their operational performance.
Greater Insight
Data discovery provides a complete picture of a company’s data streams. However, when we discuss greater insight, we also refer to the fact that data discovery enables more people in your organization to understand data analysis regardless of their technical data literacy.
When business users from your teams can understand the analytics provided by data discovery, they can do their jobs better and make meaningful contributions to strategy meetings. You shouldn’t have to be a data expert to gain valuable data insights.
Data discovery tools level the playing field and give average business users the ability to understand high-level analytics.
Improved Risk Management
Risk management has become a critical focus for organizations as the true costs of data breaches and attacks become more obvious. Data discovery can help companies identify outliers and potential threats in their collected data. As a result, businesses can proactively manage potential threats and prevent costly data breaches.
In addition, the data discovery process can also be used to stress test an organization’s data management practices to ensure compliance with industry standards and regulations.
Automatic Classification
Organizations are collecting data from more sources than ever before. The data discovery process helps businesses automatically classify the data they collect. This enables organizations to look closely at specific data points and streams. For example, businesses can break down user data collected by their website and app to better understand what measures are and aren’t working on each platform.
Final Thoughts
Data discovery is an important process for businesses with multiple data streams. If you want a comprehensive overview of your company’s data, the data discovery process is the way to do it. If you want to learn more about implementing a winning data discovery process in your business, reach out to an experienced app development partner.
