Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. However, managing evolving data requirements has become more difficult with predefined data models and rigid schemas. Information marts, combined with data vaults can help you adapt to growing data volumes and user demands and deliver insights swiftly and iteratively.

What are Information Marts?

Information marts (also called data marts) are data structures optimized for reporting and analysis. They are built on top of specialized data warehouses called data vaults, allowing users to customize and modify data and reports.

Information marts are designed to meet the needs of specific groups by having a narrow subject of data. For instance, an information mart specialized in sales will contain data related to sales performance, such as revenue, orders, customers, products, regions, and channels. This allows sales teams to access critical insights quickly and easily, without searching the entire data warehouse. According to IBM, information marts can help your team reduce costs, improve efficiency, and enable tactical decision-making.

The data vault stores raw data, while the business vault applies business rules, and transformations to the data. Typically, the data vault is not optimized for reporting and needs information marts to transform and aggregate data for analysis.

Information Mart Design

Information usually follows a star schema or a snowflake schema, which are simple and intuitive structures containing fact tables and dimension tables. Fact tables store quantitative measures or metrics, while dimension tables store descriptive attributes or dimensions.

A fact table stores metrics critical to the business operation, such as sales transactions, costs, revenue, and profits. Dimension tables provide additional context to this information.

A sales transactions table may be connected to dimension tables that illustrate different aspects of the transactions, such as products, customers, regions, and dates. Therefore, users can aggregate sales transactions by customers, products, regions, or dates.

Furthermore, information marts deliver focused, business-centric data to end-users like analysts, managers, and executives. This helps organizations create BI pipelines with access to historical data.

This design approach also supports various types of analysis, such as descriptive, diagnostic, predictive, or prescriptive. Analytics teams can also visualize these insights by leveraging reporting and visualization tools, such as dashboards, charts, or graphs.

Why are Data Vaults and Information Marts Crucial in the BI Ecosystem?

Data vault uses a hub and spoke architecture to simplify the intricacies of data integration and storage. Its versatility enables users to seamlessly manage diverse and ever-changing data sources, formats, and structures, all without disturbing existing data or structures.

The data vault architecture ensures both scalability and high performance. Techniques like parallel loading and hash keys optimize the data loading process, improving the efficiency of BI pipelines.

Data vault goes a step further by preserving data in its original, unaltered state, thereby safeguarding the integrity and quality of data. Additionally, it allows users to apply further data quality rules and validations in the information layer, guaranteeing that data is perfectly suited for reporting and analysis.

Learn whether you really need data vault.

Information marts are an extension of the data vault in the information layer. They bridge the gap between the raw data and the business insights by offering a fast, reliable, and user-friendly way to access, analyze, and visualize the data.

Moreover, data vault allows users to optimize information marts for reporting and analysis by applying various transformations, aggregations, calculations, and filters to tables. Information marts can also include additional data sources outside the data vault, such as external or unstructured data.

Information marts enable analytics teams to leverage historical data for analysis by accessing the full history of changes and transactions stored in the data vault. This allows them to perform time-series analysis, trend analysis, data mining, and predictive analytics.

Similarly, information marts can also support different types of analysis, such as descriptive, diagnostic, prescriptive, and exploratory, by providing different levels of detail, granularity, and dimensionality. Information marts are flexible and agile, as they can be easily created, modified, or deleted without affecting the data vault or other information marts.

How Information Marts Enable Agile, Scalable and Accurate BI Ecosystems

Information marts also play a vital role in enhancing three key aspects of BI: scalability, agility, and accuracy. Here’s how:

• Scalability through Data Segmentation: Information marts segment data to cater specifically to the needs of different business units or departments. Each mart operates independently, allowing for modular scalability. By dividing data into manageable segments, information marts facilitate scalable BI. As the organization grows, new or existing marts can be added, ensuring scalability without overhauling the entire BI infrastructure.
• Agility via Tailored Data Delivery: Information marts offer tailored datasets, allowing users to access and analyze information that aligns precisely with their requirements. This tailored approach is central to agile BI practices. Users can rapidly obtain the insights they need without wading through irrelevant data. This user-centric approach, facilitated by information marts, supports agile methodologies like iterative development and continuous delivery, promoting a responsive BI environment.
• Accuracy through Data Governance: Information marts empower data owners and stewards to control and maintain data quality within their domains. Governance practices, including data quality rules and security policies, are enforced at the mart level. The accuracy of BI is safeguarded by information marts governance mechanisms. Data quality is upheld, and compliance policies ensure accurate and reliable information is delivered to decision-makers, fostering trust in the BI outputs.

The Role of Information Marts in BI

Imagine a hypothetical healthcare organization, CareOrg, providing care to a vast patient community. With over 20 hospitals, 260 physician practices, 4500 affiliated physicians, and a team of 25,000, CareOrg is all about boosting the health and happiness of the communities it serves.

CareOrg stores clinical data in a data vault, collecting data from various sources such as electronic health records, labs, pharmacies, radiology, billing systems, public health agencies, and contact tracing apps. Inside, there is patient info, medical histories, lab results, treatments, and more. However, the data in this vault is raw and not optimized for reporting and analytics.

The data vault and information marts work together to enable the organization to monitor and manage the spread of infectious diseases such as dengue, COVID-19, influenza, tuberculosis, measles, etc.

The data vault integrates data from different sources and preserves the history and lineage of the data. The information marts provide a tailored view of the data for each disease, focusing on key metrics such as infection rates, mortality rates, vaccination rates, risk factors, and outcomes.

This is important because it helps the organization track the trends and patterns of infectious diseases, identify high-risk populations and regions, evaluate the effectiveness of interventions and policies, and improve the quality of care and prevention.

For example, the data vault blends information from diverse sources like electronic health records, claims, surveys, social media, and wearable devices in managing an outbreak. On the other hand, information marts help create specialized analytical reports for each disease, showing the current situation and projections of the outbreaks.

The dynamic duo of data vault and information marts helps the organization enhance the population health management for various infectious and chronic diseases.

This helps the organization detect outbreaks more quickly, manage chronic diseases, and create targeted plans for each group. Think of it like having personalized health plans for different groups, all based on what the data says.

Other Real-World Use Cases

Information marts have been successfully used by many organizations across various industries and domains for BI purposes:

• Marketing Analytics: A retail company uses an information mart to analyze its marketing campaigns across different channels, such as email, web, social media, or mobile. The information mart contains metrics such as impressions, clicks, conversions, revenue, cost, ROI, etc., as well as dimensions such as campaign, channel, product, customer segment, location, etc. The company uses this information mart to measure the effectiveness of its marketing strategies, optimize its marketing mix, segment its customers, personalize its offers, etc.
• Sales Forecasting: A manufacturing company uses an information mart to forecast its sales for the next quarter based on historical trends and current opportunities. The information mart contains metrics such as sales volume, sales value, sales growth, margin, etc., as well as dimensions such as product line, product category, product type, customer industry, customer region, etc. The company uses this information mart to apply various models or scenarios to predict its sales performance, identify potential risks or opportunities, allocate resources accordingly, etc.
• Risk Analysis: A financial institution uses an information mart to perform a risk analysis on its portfolio of loans across different countries and sectors. The information mart contains metrics such as exposure amount, default probability, loss given default, expected loss, etc., as well as dimensions such as loan type, loan status, loan rating, country, sector, etc. The institution uses this information mart to perform various calculations or simulations to assess its risk profile, manage its capital adequacy, mitigate its credit risk, etc.

A Final Word

Information marts are indispensable assets in BI. They help organizations leverage data warehouse as a reliable repository for analysis and reporting in the face of increasing volumes of data and evolving business rules. Meanwhile, organizations remain compliance ready and maintain a rich source of historical data for accurate analysis and forecasting.

Are you looking for a no-code solution to create and manage your business intelligence (BI) pipelines? Astera is a unified data management platform that lets you build your own data vault and information marts within minutes. Learn more about Astera and how it can help you turn data into insights at lightning-fast speed. Click here to start your free trial or schedule a demo.