Initiating Your Catalog Journey
Business intelligence and analytics are key to the data-driven decisions that executives and knowledge workers make every day. However, with multiple users running multiple reports across multiple BI platforms, analytics leaders struggle to measure the return on their various investments, identify who is using what tools and for what purpose, and track overall user adoption.
Fortunately, a new breed of technology has emerged to provide BI and analytics managers and executives the insights they need to drive BI adoption for maximum ROI.
Analytics catalogs are complementary to data catalogs and play a similar role, albeit with BI and analytics assets rather than data assets. Data catalogs emerged earlier this decade to provide chief information officers, chief data officers, and chief security officers a holistic view of how their ever-growing data assets were being used throughout their organizations and provide a level of control over all their data assets. Now, analytics catalogs are providing a similar view of BI and analytics assets for BI leaders, IT managers, data executives, and governance teams. While analytics catalogs are a relatively new technology, results have been extremely positive. Early adopters have referred to their analytics catalog as “a gamechanger” for their BI programs in terms of adoption and ROI.
Analytics catalogs provide a single pane of glass for users attempting to access information hosted in multiple platforms. They enable knowledge workers a more productive and collaborative working environment, leading to an increased confidence in their decisions. Additionally, executives can identify which team members are leveraging which reports and platforms so they can drive adoption and improve ROI.
Read on to learn about the new technology category of analytics catalogs, how they compare with data catalogs, where you should get started, and how a real-world implementation drove BI adoption and ROI.
What is an Analytics Catalog?
According to Gartner, analytics catalogs “combine portal-like capabilities with curation and collaboration functions and applies them to analytics and BI content. This enables users to share, find, search, comment, and rate dashboards, reports and datasets from a diverse range of platforms in one place. They also help those managing portfolios of analytics and BI platforms to monitor, manage and migrate usage across technologies.”
The value of an Analytics Catalog and how it complements — but differs from — a Data Catalog.
By organizing enterprise resources in a personalized and structured way, analytics catalogs enable productivity, collaboration, manageability and governance around BI and analytics platforms. Within a single interface, an analytics catalog provides direct access to all analytics assets to which a user has permissions, such as reports, dashboards, spreadsheets, and applications.
For governance teams, analytics catalogs reduce the likelihood of data being exported to Excel. Often, BI end-users will export data from one platform because they want to use it in another platform. However, if the analytics asset already exists in the other platform, the end-user would easily see that through the analytics catalog.
Use Cases for Analytics Catalogs
Rather than logging into multiple applications to find an important report or visualization, users can enter their analytics catalog portal and find the information they need across all BI environments. As the central portal for all things BI, the analytics catalog captures metrics and metadata about the usage of each environment, so executives can make informed decisions on future analytics investments.
Analytics catalogs provide robust capabilities for multiple groups, including BI users, executives, and governance professionals. Therefore, there are multiple use cases for analytics catalogs, typically centered around BI adoption, ROI, and security.
For knowledge workers
- Report personalization
- Unified reporting
For information stewards
- Mergers and acquisitions
- Self-service report governance
For management and executives
- Tool consolidation and optimization
What is a Data Catalog?
Standalone data catalog applications predate analytics catalogs by several years, though some data warehousing providers have provided solution-specific catalogs for longer. Standalone data catalogs became necessary as organizations entered the big data age and saw the sprawl of data across multiple data warehouses, data marts, and data lakes such as Hadoop. Typically, this view could run across assets as diverse as a Teradata data warehouse, Hadoop-based data lake, cloud-based OLTP databases, and more.
Data catalogs are not meant to provide access to dashboards, reports, or data science notebooks. They exist primarily to categorize and govern data.
Example Use Cases for Data Catalogs
Data catalogs are useful for knowledge workers who want to find trusted data sets, governance professionals who need to ensure that sensitive data is secure and protected, and IT leaders who need to know where data resides for a variety of reasons.
Data catalogs can deduce or document data lineage, and they enable users to collaborate on data based on its source. They may leverage machine learning to improve their understanding of data sets and the metadata around that data.
Analytics catalogs and data catalogs are highly complementary. They essentially serve similar purposes for different types of assets. Together they will provide a holistic view of all information assets, they can provide end-to-end governance, and help optimize the use of all information assets. While an analytics catalog’s strength lies in its understanding of your analytics assets and the usage of reporting platforms, data catalogs focus on a lower-level layer at the underlying data source.
The Complementary Relationship of Analytics Catalogs and Data Catalogs
How Analytics Catalogs and Data Catalogs can Work Together
Often different teams - and sometimes the same teams - need insights into different levels of data and reporting infrastructure for different reasons. For example, knowledge workers might find a report that leverages an out-of-date data set, then rebuild the report with a current data set and publish it throughout the analytics catalog. They then may want to look at the data catalog to downrate the old data set and promote the current data.
Conversely, a user may begin their journey in the data catalog to find the most up-to-date data and identify any reporting content built on that data. Then in the analytics catalog, they could promote the accurate current reports to make them easier to find for colleagues.
These are just a couple of how analytics catalogs and data catalogs can provide real value in complementing each other, though there are many more to be explored as the providers behind both categories of technology continue their development.
How to Prioritize
End maintenance, hosting, and other costs of unused reports.
Catalog and Organize all Information Assets
Many companies are on the verge or in the midst of implementing an analytics catalog, a data catalog, or both. If you haven’t already started, you may now be asking where to begin.
Optimize Information Resources
By making analytics assets available and searchable and being able to track their use, you can reduce costs in three key areas fairly quickly.
Starting with an Analytics Catalog
Every organization is unique. To drive the biggest ROI, consider how to structure your data catalog project tackling the most important investments.
Augmenting your Data Catalog with an Analytics Catalog
While analytics catalogs are a relatively new category of technology, they are quickly proving their value. If you are like the majority of organizations that have implemented multiple analytics and reporting platforms, starting with an analytics catalog can further increase adoption transparency and ultimately the ROI of your data stewardship.
Conclusion
While analytics catalogs are a relatively new category of technology, they are quickly becoming essential in the toolkit of organizations aiming to improve BI adoption and return on investment.