How IBM Data Product Hub helps you unlock business intelligence potential

Business intelligence (BI) users often struggle to access the high-quality, relevant data necessary to inform strategic decision making. These professionals encounter a range of issues when attempting to source the data they need, including:

• Data accessibility issues: The inability to locate and access specific data due to its location in siloed systems or the need for multiple permissions, resulting in bottlenecks and delays.
• Inconsistent data quality: The uncertainty surrounding the accuracy, consistency and reliability of data pulled from various sources can lead to risks in analysis and reporting.
• Time-consuming data requests: The reliance on data engineering teams to fulfill data requests can lead to delays of days or even weeks, hindering the reporting process.
• Lack of transparency on data use terms: The absence of clear guidelines and regulations surrounding data use can lead to compliance risks if data is used improperly or outside its intended scope.

These challenges can have a far-reaching impact on an organization’s ability to make informed decisions. Consequences include:

• Lost productivity: Wasting time and resources searching for data that is not readily available.
• Inaccurate insights: Undermining of the reliability of analysis and reporting due to inconsistent data quality.
• Delayed decision making: Hindering strategic decision making due to slow data access.
• Compliance risks: Exposing organizations to potential fines and reputational damage due to the lack of transparency on data use terms.

By using the power of data marketplaces and data products, organizations can unlock faster, more reliable access to high-quality data, ultimately driving faster and more informed decision making. Data marketplaces are designed to solve these challenges by allowing organizations to package and distribute data as data products. Data products are managed, governed collections of datasets, dashboards and reusable queries. They are designed to be readily used by business executives, business analysts, data analysts and other data consumers for analytics, AI and other critical data workloads. These products are easily discoverable, consistent, and can be governed through predefined data contracts.

IBM Data Product Hub is a data sharing solution that enables data producers to create and manage data products. These products are curated with key attributes such as business domain, access level, delivery methods, recommended usage and data contracts.. It empowers users of data lakehouses and data warehouses to package their data assets as data products, simplifying data sharing and access.

The data contract feature helps ensure that data can be shared with consumers in a governed and transparent way, providing a clear understanding of usage permissions and terms. By packaging assets as reusable data products, data producers no longer need to repeatedly fulfill similar data requests, improving efficiency.

This approach accelerates access to high-quality data from disparate data sources for consumers, reducing the wait time. The data products are reusable in nature, saving storage and processing costs of curated assets in data lakehouses.

The capability to package assets stored in data lakehouse as data products on Data Product Hub enhances the ability to harness data from a data lakehouse. Data products are accessible across the organization, resolving pain points for both business and technical producers.

Data producers can deliver data products to data consumers by using either data extract or live access using flight service delivery method. Data consumers can review business use cases, key features and data contracts associated with a data product and place a subscription request.

In the current release of Data Product Hub, a technical data consumer can create BI reports by using data products delivered using flight service delivery method that enables live data access without data movement. The consumer can create a “Python script” connection in Microsoft Power BI and start creating BI reports for further BI analysis on data products. When the Python script runs in Power BI, the user authenticates themselves to the server by using the JSON string shared with them during data product delivery. This allows live read-only access to data assets stored in a data lakehouse from within Power BI.

To find more details on how live access using flight service works and how it can be used to connect to Microsoft Power BI, take a free trial of Data Product Hub.

For BI users, IBM’s new data sharing software offers a modern approach to overcome the traditional pain points of accessing data. By packaging curated, high-quality data assets as data products, organizations can help ensure efficient, governed and consistent data delivery. This allows BI users to generate reports faster, with greater confidence in the quality and governance of the data they are using—ultimately driving better business outcomes.

Are your data teams struggling with data accessibility, quality issues or slow reporting cycles? Register for our webinar series where we discuss data sharing best practices to help you unlock the full potential of your data.

Want to gain hands-on experience with the powerful features of Data Product Hub? Take a free trial today, or talk to an IBM expert to learn how you can supercharge your data-driven outcomes.