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Why do you need a data catalog?
Easily Find and Share your data with Precisely Data360 Catalogue and Data Governance platform. An enterprise data catalogue should be much more than a repository of technical data assets. A business-first data catalog acts a a true 360-degree view of data across the enterprise, opening new possibilities for the use of data, and is increasing one of the most essential business intelligence tools for any organisation.
Table of Contents
- Benefits of data catalogues
- Choosing the right Data Catalogue
- A world-class catalogue ensures data integrity
- Precisely Customer Spotlight: Northwest Bank sets gold standard for data quality & data governance
- FAQ about data catalogues
- What is a data catalogue?
- What are the benefits of using a data catalogue?
- What types of data assets can be included in a data catalogue?
- Data Governance vs Data Catalog: What’s the Difference?
- Business Glossary vs Data Catalog: What’s the Difference?
- Data Modelling vs Data Catalog: What's the difference?
- Will my data catalog support my enterprise ERP and CRM, like SAP, Dynamics CRM or Salesforce?
- What features should I look for in a data catalog?
- How will my catalog support my BI team?
Benefits of data catalogues
Data catalogues are essential tools for managing data assets and understanding data in organizations. Data catalogues provide a centralized repository for metadata management, including technical metadata and business terms. They help data scientists, data analysts, and other stakeholders find the data they need and ensure trusted data access.
One of the key benefits of data catalogues is that they provide a single source of truth for data lineage and data quality. Data lineage helps organizations understand the origin and transformation of data, while data quality ensures that data is accurate, complete, and consistent. By maintaining data lineage and data quality in a data catalogue, organizations can ensure that their data is trustworthy and can be used for business decisions.
Data catalog tools typically include features for data discovery and data access. With data catalog tools, data scientists and analysts can easily find the data they need and access it quickly. This can help reduce the time spent on data discovery and allow stakeholders to focus on analysis and insights.
Data governance is another key aspect of data catalogues. By maintaining sensitive data and ensuring compliance with regulations, data catalogues help organizations manage their data assets effectively. Data governance policies can be enforced within a data catalogue, ensuring that sensitive data is protected and that data access is restricted to authorized users.
In summary, data catalogues are essential tools for managing data assets and understanding data in organizations. They provide a centralized repository for metadata management, data lineage, and data quality.
With data catalogue tools, stakeholders can easily find the data they need and ensure trusted data access. Data catalogues also help organizations manage data governance policies and protect sensitive data.
Read our guide on Business Intelligence Tools for a comprehensive list of other tools that can also help you enhance your business intelligence efforts.
Choosing the right Data Catalogue
Precisely Data360 Catalog empowers business and technical users to quickly find and understand the data that they need to do their job and deliver business insights. The IDC recommends that Precisely should be considered “when looking for a business-focused solution with integrated data catalog, data quality, and data integration capabilities.”
Read this Precisley eBook to learn the basics of what a catalog is and how it works, what business challenges it can help solve, and how to make sure you are avoiding common pitfalls and choosing the right catalog for your needs.
What makes the Precisely Data Catalog so different?
Documenting ROI by connecting business initiatives with critical assets
Building trust with dynamic data governance and quality metrics
Ramping up onboarding and adoption with flexible metamodel
Optimizing insights into data pipelines, lineage, and observability
Implementing successful data programs with strategic services expertise
Stop wasting time and unlock new possibilities
According to Gartner, professionals spend half of their time searching for information
Another study by IDC reveals that knowledge workers spend around 2.5 hours per day, which is approximately 30% of their workday, searching for information. Whichever number you believe, an alarming amount of time is wasted when expensive knowledge workers cannot find the information that they need to do their job.
A business-friendly catalogue brings order to the chaos, increasing productivity and creating new possibilities.
Quickly acquire and manage data.
Use Precisely Data360 to automatically discover, harvest and catalogue all accessible data. Translate technical metadata into business information that can be used by anyone.
Automated metadata harvesting:
Quickly crawl, profile, score and manage complex metadata. You’ve then built a single, searchable inventory of data assets for future use. Use existing rules to automatically identify and tag personal information and other data types, or add your own rules for your unique data sets
Make your data work for you
Improve decision-making by increasing productivity, accuracy and understanding of all available data. Share data without losing control.
Machine-learning search and discovery
Simple and intuitive search for users to quickly find data assets. Eliminate wasted time struggling to access the quality data you need.
The comprehensive data governance structure defines data owners, established policies and their interconnections, allowing data consumers to identify the appropriate authority to approach for data-related queries.
Manage access to data sets and reports
Automated workflows route access requests and manage audit trails for access to any data element.
A world-class catalogue ensures data integrity
Every data catalogue will provide the ability to gather and arrange important data assets.
However, for an optimal solution that facilitates the efficient delivery of reliable data throughout the entire organisation, it's important to incorporate a data governance framework, integrate data quality, and provide analytics support. Where many catalogues are restricted to a particular technology stack, an enterprise catalogue must provide context for data coming from across, and even outside, the enterprise.
Users that have confidence that data has optimal integrity, that can easily find and compare alternatives, and that are able to communicate seamlessly with the data owner, subject matter experts, and other stakeholders, are more comfortable using that data to drive insights, with less dependence on IT or other technical support.
Precisely Customer Spotlight: Northwest Bank sets gold standard for data quality & data governance
FAQ about data catalogues
A data catalogue is a centralised inventory of data assets that provides metadata about the data, such as its location, schema, data quality, and lineage.
Using a data catalogue can provide a number of benefits, including:
- Improved data discovery: A data catalogue can help users quickly find the data they need.
- Increased data accuracy: By providing metadata about data quality, a data catalogue can help users identify and avoid using low-quality data.
- Enhanced collaboration: A data catalogue can facilitate collaboration among data users and stakeholders.
- Reduced time-to-insight: A data catalogue can help users get up and running with new data sources more quickly.
- Better governance: By providing information about data lineage and ownership, a data catalogue can help ensure compliance with data governance policies.
What types of data assets can be included in a data catalogue?
A data catalog can include a variety of data assets, including:
- Databases and tables
- Files and documents
- APIs and web services
- Reports and dashboards
- Data models and schemas
- Business glossaries and data dictionaries
Data360 can be easily extended, without writing any code, to include support for any asset or relationship that you need to track.
Data Governance vs Data Catalog: What’s the Difference?
There are clear connections between building a data catalogue and data governance.
Data catalogues are a dictionary of knowledge about the data and processes an organization uses to manage and consume data. Data catalogues arrange data into a simple, easy-to-understand format so all data users can consume and use it.
A data catalogue is a core component of data governance.
While data governance identifies data owners, stewards, and users, the data catalogue shows the data assets of an organization and where they’re located. In a nutshell, it helps users get a handle on their data.
In addition, enterprise data catalogues like Data360 Govern implement the data governance organisation and processes directly with the catalogue, making sure that critical data assets are appropriately governed and leveraging automation to simplify the processes.
A data catalogue is a repository of metadata that provides an inventory of all the data assets within a specific scope, regardless of its location or source. The data catalogue includes information about key elements that give business context and make it easy for users to understand what they are working with.
A business glossary is a repository of business terms and definitions. A catalogue will typically include a business glossary but adds much more.
Data modelling tools help the data modeller to manage the complexity of modelling a typical enterprise data landscape, keep a graphical record of the design, and provide a template to the developers for implementation. The users tend to be technical in nature, although models can be useful tools to communicate with business stakeholders.
A data catalogue, by comparison, supports a bottom-up approach to database design. Data catalogues leverage algorithms to discover actual data models and present them to the data modeller and the business.
Humans can then add business context, such as the business systems, processes and reports that use or populate the data set. Where data models did not previously exist, this automated approach can save tremendous time and effort when documenting a data landscape.
Data catalogues help to make data visible within and across the enterprise, both by providing a physical location and by providing the business context necessary for data scientists, analysts and decision-makers to find the best set of data for a particular requirement.
Data catalogues present a single source of truth for all things data, automate stewardship workflows and provide audit trails for decision making.
Will my data catalog support my enterprise ERP and CRM, like SAP, Dynamics CRM or Salesforce?
Data catalogues can connect a database level to any application for which the database is accessible.
However, in practice, the data models of commercially available ERP and CRM systems are vast and obtuse. Pulling the raw data models into a catalogue is not helpful. We use Safyr to covert the "raw" views to add business-friendly names and relationships, making ERP and CRM metadata accessible and valuable, and feeding this useful information into the catalogue.
What features should I look for in a data catalog?
When evaluating data catalogs, look for features such as:
- Search and discovery capabilities
- Automated data profiling and metadata extraction
- Collaboration and social features
- Easy integration with other data tools and platforms
- Data lineage and impact analysis
- Data governance and security features
- Dashboarding and metrics
- Easily extensible workflow
- Ease of extension of the operating model
How will my catalog support my BI team?
An enterprise data catalog provides a complete picture of your data landscape. making it easier for your BI team to find the data sets and reports they need.
Whether you are implementing BI in the Cloud, or on-premise, your data catalogue should allow you to find data sets, manage access, and build business context.