How do data discovery and business intelligence work together? The two analytic tools are similar in approach even though they have subtly different uses in your organization. Data discovery has growing applications in business intelligence – if you know how to integrate the two tools.
- Business intelligence and data discovery both consolidate data from multiple sources
- Business intelligence is better used to generate general insights for day-to-day operations
- Data discovery is best used for in-depth analysis of specific issues
- Data discovery uses data visualization to help users more easily understand detailed analysis
Business Intelligence: What It Is and Why It’s Important
Business intelligence (BI) is a process for gathering, organizing, and analyzing data with the goal of delivering actionable insights. BI lets management and other staff query the collected data, generate detailed reports, and visualize data via the use of dashboards. Companies use BI to better run their businesses on a day-to-day basis.
How Business Intelligence Works
Business intelligence involves the use of a variety of technologies and tools. It’s typically a five-step process that involves:
- Collecting data from various sources
- Integrating and organizing the collected data
- Analyzing the data
- Visualizing the insights provided by the data
- Using the data for better decision-making
The first step in BI is data collection, and it can be costly. Data is typically found in a number of different systems and department silos, in a variety of file formats, both structured and unstructured. (According to multiple sources, 80% to 90% of all data is unstructured, which makes it challenging to extract value from.)
To be of value, this disparate data must be integrated into a single data warehouse and organized in a logical fashion. The data must also be reviewed and cleansed so that it is consistent, accurate, and complete. For this stage of the process, Data quality management is essential for ensuring the necessary high data quality.
The integrated data can then be analyzed, using a variety of BI tools. Some of these tools use artificial intelligence (AI) and other advanced technologies to extract actionable insights from the data.
To make the data more useful, it must be presented in a way that is easily understood by management and key staff. While some staff still request detailed reports, management is typically better served by a more visual presentation. Reporting from the Marketing Vision 2021 conference confirms that visual dashboards and reporting are a top priority for organizations in all industries.
With all this information and analysis in hand, management and staff can make more informed decisions for day-to-day operations. This is the ultimate goal of business intelligence.
Benefits of Business Intelligence
Business intelligence provides numerous benefits to organizations of all types. The benefits include:
- Provides faster insights
- Enables easier identification of trends (thanks to data visualization)
- Enables smarter operating decisions
- Enables analytics and insights deeper in the organization, thanks to embedding analytics in business practices
Data Discovery: What It Is and Why It’s Important
Data discovery is a subset of business intelligence. Like BI, data discovery involves collecting data from a variety of databases, consolidating it into a single source, and using it to provide visibility into various aspects of your business. This visibility helps identify key factors and trends and uses that information to make more informed business decisions.
How Data Discovery Works
Data discovery is essentially a three-step process, as follows:
- Data is collected and prepared for use; this includes integrating data from multiple sources, cleansing the data, and presenting it in a format that is easy to query and use.
- Data is visualized in the form of visual dashboards, charts, diagrams, and other media.
- Advanced analytics organizes and summarizes the data into simple reports to aid in decision making.
To provide actionable insights, data discovery relies on a number of sophisticated data analysis skills, including data modeling and guided analytics. The use of visualization techniques and intuitive reporting makes it easy for non-technical users to quickly grasp and absorb key trends and data.
A data discovery platform typically includes the following features:
- Advanced data analysis tools
- Data visualization tools (dashboards, charts, tables, etc.)
- Predictive analytics
- Automatic data identification and classification
- Full-text and metadata search
- Data quality management, including metadata management
Benefits of Data Discovery
How does the use of data discovery benefit your business? The benefits are similar to those of BI, in general, and include:
- Ability to visualize datasets, trends, and outliers
- Provides automatic classification of data
- Offers broad access to data insights across the organization
- Enables a bigger picture view of key data
- Improves regulatory compliance and risk management
How to Use Data Discovery in Business Intelligence
Data discovery democratizes business intelligence. By providing easy-to-grasp data visualizations, data discovery makes it easy for users at any level to better understand key business trends and take advantage of advanced analyses.
Comparing Data Discovery and Business Intelligence
Data discovery and business intelligence serve two similar but distinct functions in an organization.
The similarities are significant. Both business intelligence and data discovery consolidate and normalize data from a variety of sources, including databases siloed in individual departments. Both BI and data discovery hep to maximize the value of your organization’s data. Both provide valuable analysis and insights
The differences are also significant:
- Business intelligence provides a more consistent flow of information to support day-to-day decision making
- Data discovery is better at providing one-off, on-demand analysis of key data and trends
When considering adoption, organizations should take into account the “single source of truth” available in BI solutions, the skill sets required for each solution, and BI solutions that integrate discovery as well traditional reporting and dashboard capabilities.
When to Use BI vs. Data Discovery
Both business intelligence and data discovery start by collecting and consolidating all available data and converting it into a standardized and usable format. From there you can choose either BI or data discovery tools, depending on what you aim to achieve.
You should employ BI tools to:
- Provide enterprise-wide reports
- Generate real-time data for use in day-to-day operations
- Identify long-term trends
- Share general information with a wide range of users
You should use data discovery tools when you want to:
- Provide tactical analysis
- Provide answers to specific business-related questions
- Dig deep into specialized data investigations
- Analyze data from unstructured sources, such as social media
- Share specific analysis with a limited group of users
In short, business intelligence provides general information useful across the enterprise, where data discovery provides detailed information based on specific analysis. They both have their places in your organization.
(The following video goes into more detail about how data discovery is changing business intelligence.)
Let DataBuck Provide High Quality Data for Both Data Discovery and Business Intelligence
Whether you need the general information provided by business intelligence or the specific answers afforded by data discovery, you need to start with high quality data. To ensure the highest possible data quality, turn to DataBuck from FirstEigen. DataBuck is a data quality management solution that can automatically validate thousands of data sets in just a few clicks. It can identify bad data and either clean it or isolate it, as well as constantly monitor new data fed into your data pipeline. When you need clean data for BI and data discovery, turn to the data quality experts at FirstEigen. Contact FirstEigen today to learn how FirstEigen can help ensure better BI and data discovery results.
Check out these articles on Data Trustability, Observability, and Data Quality.
- 6 Key Data Quality Metrics You Should Be Tracking (https://firsteigen.com/blog/6-key-data-quality-metrics-you-should-be-tracking/)
- How to Scale Your Data Quality Operations with AI and ML (https://firsteigen.com/blog/how-to-scale-your-data-quality-operations-with-ai-and-ml/)
- 12 Things You Can Do to Improve Data Quality (https://firsteigen.com/blog/12-things-you-can-do-to-improve-data-quality/)
- How to Ensure Data Integrity During Cloud Migrations (https://firsteigen.com/blog/how-to-ensure-data-integrity-during-cloud-migrations/)