Organizations are drowning in data but starving for insights. All business stakeholders are looking to maximize the utility of their data assets. Data catalogs are a powerful tool that can help businesses on their journey to good data governance. With powerful functionalities that can speed up data discovery, automate actions, provide insight and help ship analytics, data catalogs are setting the gold standard in the data management category. Modern data catalogs must contain five critical pieces of information. Continue reading to find out.
All companies are data companies. Whether it be a large multinational giant like Apple or Microsoft or a small Tailor selling his cloth work, each one of them is in the business of data creation, interpretation, utilization, and management. Decision-makers in companies today face a new challenge – How do they use their significant data assets to gain insight and drive data-driven decisions? In a competitive market, one with proprietary information has the upper hand. Then, how exactly do data leaders achieve their goals? There are numerous ways. They could establish a robust data governance program, build or purchase tools and software, hire a dedicated data team, or even leverage third-party or syndicated services. With all of these possible solutions offering different capabilities, how do leaders decide which one is right for them?
Similarly, those professionals who live and breathe data daily understand the everyday frustrations and bottlenecks they face when working on any data project. Listed below are some of the most common complaints from data analysts, engineers, and scientists:
- Slow speed of data discovery
- Lack of visibility into data assets and lineage
- Insufficient understanding of underlying data and key metrics
- Incomplete and inconsistent data
- No metadata management guidelines
Solutions to these problems are often more straightforward than they seem, provided that the right tools are utilized.
What if a single tool could address all their business requirements in a seamless, easy-to-use solution? One of the most powerful tools businesses can leverage is modern data catalogs. A Gartner report describes Data Catalogs as the new black in Data management and analytics.
But, what are modern data catalogs?
To start, data catalogs are tools that organize and inventory all data assets in their organization while providing descriptive information, insight, and transparency. When combined with powerful artificial intelligence functionalities, Modern AI-driven augmented data catalogs are part of these solutions, automating metadata discovery, ingestion, translation, enrichment, and the creation of semantic relationships between metadata. To put it simply, they are much more powerful and robust versions of the same data catalog that we know and use.
Let’s review the top 3 features that modern data catalogs must contain:
1. Automation and ML/AI
Modern catalogs should have the ability to automatically Scan your databases, data lakes, BI Reports, and applications. They should be able to seamlessly harvests the metadata, profile the data, classify it on multiple characteristics, link it to other data and to other data domains. Many catalogs contain AI-enabled classification algorithms that will automatically connect the physical data elements to the glossary terms and recommend enrichments to the business glossary. Making data cleansing easier by semantically tagging data and inferring relationships helps data analysts and scientists immensely. Lastly, a modern data catalog must be able to recommend the data quality rules automatically. It can check for unexpected schema, quality, volume, and distribution of data.
2. Active metadata
Active metadata is essential to keep a Modern data catalog refreshed. Active metadata is Machine learning augmented metadata that enables actionable insight from metadata. Active data has powerful benefits, including Automatic metadata harvesting, data classification, and prioritization. Lean governance tailored to business needs is easily achievable through dynamic metadata.
3. Crowd-sourcing curation of catalog
When selecting a data catalog, it is essential to be part of a passionate and widespread adoption community that helps build and review the tool that they use. Having peers that not only consume the same tool but also contribute to the catalog directly helps to make the user experience even better. Building applications and reports that are available for other users to consume ensures that the tool and community grow.
To sum up, modern data catalogs are potent tools that can help accelerate the journey to good data management.
