A data catalog represents the foundation for finding, understanding and managing data assets across the enterprise. As analytics becomes increasingly central to decision making, a high quality catalog is absolutely essential. This comprehensive 2600+ word analysis covers everything needed to architect, implement and operate an effective business data catalog.
Defining Data Catalogs
A data catalog consists of an organized metadata registry describing the information scattered across an organization‘s databases, files shares, cloud platforms and other properties. The central catalog acts as an index to these distributed data resources by capturing attributes like:
- Lineage – Data origins and processing/modification history
- Owners and Stewards – Business data authorities
- Structures and Formats – Schema details, locations etc.
- Update Frequencies – Batch vs real-time
- Data Volumes – Row counts, storage usage
- Confidentiality and Security – Privacy & compliance status
Tagging data assets according to consistent taxonomies facilitates discovery by category or business terms in addition to searching technical metadata. Association with organizational KPIs tracked in various reports or dashboards also increases contextual relevance.
The Critical Need for Data Catalogs
With data volumes and sources multiplying each year, organizations cannot afford employees wasting countless hours hunting down information vital to their jobs. Surveys indicate analysts spend nearly 30% of time simply finding and preparing data. Extrapolating to entire enterprises means staggering losses from such data discovery friction.
By centralizing access to institutional knowledge around available data in one reliable system of record, companies can finally shed legacy complexity that has frozen assets into isolated silos. Integrating catalog platforms with familiar business tools through context menus enhances natural adoption. Collaborative tagging further bridges discontinuities using common language.
The urgency only accelerates as governance mandates require means to inventory data locations together with who can use information and when. Having catalog visibility into related datasets also facilitates vital integration across units, systems and reports which multiplies productivity.
Key Business Benefits
Beyond finding enterprise data faster, well executed catalogs confer additional advantages:
- Accelerates analytics workflows – Quick access to info needed for modeling and decisions.
- Cost avoidance from duplicates – Consolidating redundant datasets saves storage/processing.
- Supports self-service access – Empowers more users with transparency.
- Increased security/compliance – Controls and auditing on sensitive data.
- Foundation for data governance – Stewardship, lifecycle management, quality.
According to research firm Gartner, half of companies currently lack effective oversight into their own data landscapes. Closing this gap presents an enormous opportunity to transform latency into productivity.
Constructing the Catalog
Successfully creating sustainable catalogs requires addressing three interrelated disciplines:
Technical Indexing and Discovery
This foundational layer relies on crawlers to automatically extract metadata from databases, warehouses, file shares and SaaS applications – both on-premise and cloud-based. Look for catalog tools leveraging frameworks like Apache Atlas or flexible APIs for custom connections.
Key integration points include data integration platforms (e.g. Informatica, Talend), BI/reporting tools (Tableau, PowerBI), RDBMSs (Oracle, SQL Server), Hadoop distributions, and master data management hubs.
Auto-generated tags classify information according to configurable taxonomies. Integrating this enterprise vocabulary with glossaries and existing BI semantics enhances consistency. Additionally, usage metrics reveal popular assets to improve recommendations.
Business Context and Collaboration
While automated crawling provides scale, achieving maximum relevance requires extensive human augmentation. Collaborative tools like crowdsourcing, commenting, and annotations must capture tribal knowledge within catalogs.
Link data to organizational KPIs and objectives being measured in reports. Incorporate cross-references from related analytical projects. Beyond definitions, include examples of actual use cases, applicability and ideally business impact quantified through metrics.
Driving such participation throughout the enterprise facilitates alignment on shared language for information assets everyone relies upon. Steward designation, certification and community workflows also build engagement.
Ongoing Governance and Maintenance
With continuous updates across systems, successfully maintaining catalogs demands proactive data management. Automated notifications alert stewards to changes requiring renewed validation.
Look for platforms that synchronize indexes through batch scheduling, streaming integration and tool connectors. Rigorously quantify consumption metrics to prioritize enhancements where catalog usage proves greatest business impact.
As regulatory obligations expand, access controls, permission management and activity auditing ensure visibility complies with policies. Masking and tiered visibility provide security without completely preventing discovery.
Associated business glossaries, reference data and master entities act as hubs for maintaining connections to cataloged data elements. Quality management processes leveraging catalog metadata fuel improvements that multiply downstream value.
Leading Data Catalog Platforms
The market for commercial enterprise catalog solutions features robust options:
Informatica Enterprise Data Catalog
The longstanding data management leader, Informatica combines intelligent automation together with extensive collaborative features for continuous curation. Tight integration across Informatica‘s end-to-end platform constitutes a key strength.
Collibra Data Catalog
Oriented as the system of engagement connecting data consumers to the system of record production by IT, Collibra excels at participative workflows. The emphasis remains on total user enablement.
Alation Data Catalog
Focused on behaviorally driven recommendations and human-augmented machine learning, Alation pioneered applying collective intelligence to unstructured data challenges through crowdsourcing and similar innovations.
Other Contenders
Additional options exist for specific needs – waterline Data, Alex Solutions and Ovaledge for automation-centric use cases more narrowly focused on technical metadata, as well as enterprise platform vendors like IBM or AWS extending catalog functionality across their clouds.
Choosing the optimal tool depends on current legacy landscape, targeted endpoints, and the division of automation requirements compared to collaborative priorities. Integrations with adjacent data management capabilities may also guide direction.
Best Practices for Data Catalog Success
Extracting full value from catalogs involves considerable change management across people, processes and technology. Follow these vital practices:
Take Inventory of Existing Assets
Understand current state – what fragmentation exists between databases, files shares and reports? Document costs from data discovery delays and process bottlenecks. Establish metrics aligned to KPIs for ongoing tracking.
Involve Communities Beyond IT
Marketing, finance and other groups using analytics must help enrich business meaning within catalog systems. Without extensive participation, tribal knowledge stays siloed despite technical centralization.
Prioritize High Impact Use Cases
The most problematic areas where poor transparency causes analytics delays and decision making friction should drive initial cataloging. Quick wins build momentum for long term change.
Integrate Catalogs into Daily Workflows
Both contributors and consumers interacting with business intelligence and data integration tools should experience embedded catalog context for easier adoption. Avoid separate portals or manual processes.
Maintain Alignment with Data Strategy
Catalog initiatives support overall information lifecycle efforts from sourcing to retirement. Joint roadmaps and combined governance ensure synchronization of priorities and funding.
Govern Security and Compliance Requirements
Evolving regulations mandate stricter controls over sensitive data. Masking integration, tiered visibility and robust audit logging help balance openness for productivity against policies for confidentiality.
The Path Forward
With modern catalog solutions, organizations can finally liberate data from captive storage buckets into quantified assets activated across the business. But technology represents merely the foundation. Ultimately cultural priorities embracing openness and collaboration will determine the difference between companies still struggling versus analysts enabled.
Leaders seeking analytics excellence cannot afford chaotic opacity around mission critical information. Harnessing collective intelligence to reach shared understanding around trusted data meets the challenges of diverse sources and proliferating volume. With growing maturity, insight residency transitions from fleeting moments within individuals to permanent enterprise assets compounding over time.