#datacatalog

Prompt and timely data receipt contributes to the efficient business activity. Empowerment through the analytic data access enables a faster process for users to discover and receive information. A single, self-service data catalog from Qlik can provide analytics across the enterprise.

Qlik Catalog is a modern enterprise data management solution. The product is a single corporate data catalog that simplifies and accelerates the reliable data cataloging, management, preparation and delivery to business users. Qlik Catalog is powered by modern data warehouses and computing platforms (Snowflake, AWS, Azure, Google Cloud). The tool has a robust set of management and administration capabilities to simplify scaling, integration with other systems, and data protection.

With the help of the corporate catalog from Qlik it is possible to collect all data in one viewport. A single secure catalog of all corporate data available for analytics is created regardless of the data place. Powerful and automated data preparation tools make it easy to transform raw data into analytic information assets. The unified data catalog enables users to find, understand and use any corporate source to extract analytical information.

Qlik Catalog provides transparency, data reliability, and discoverability. Through validation, profiling and data quality assessment, the exact content and quality of each data source is documented. Easy-to-use tools enable users to quickly transform raw data into their own information sets. In addition, users can reuse, extend, and share previously created files. It allows to accelerate usage and reduce data preparation costs.

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Continuing the data catalog topic, its implications for business and data users, today we will look at modern enterprise data catalog environment characteristics.

The modern data catalog is notable for its advanced features. The application stack for enterprise data analysis mainly simplifies the process of working with data and includes the following features:

management of data asset structure metadata that includes data profiling for assessing the data asset structure, structure of existing semantic, logical and physical data models, table layout details, data elements, data size and type, etc.
management of data asset object metadata that includes the data source, owner, refresh rate, and other object elements;
business metadata of data assets includes business glossaries, semantic graphs, classifications, logical namespaces;
data intelligence utilities allow to define data asset, perform automatic discovery, identify and inventory dispersed and heterogeneous data, classify, document data lineage, generate an intelligent search index;
the data portal provides visibility to catalog information and also includes an intelligent index;
data management support including data quality management, data certification and tagging, data protection policy, access control.

The data catalog central task is to solve data source discovery problems and help business to extract full value from their information assets. With the help of data catalog, it is possible for a user of any level to discover, recognize, and use data sources. Qlik offers its enterprise data management solution «Qlik Data Catalog» that simplifies and accelerates the process of managing, cataloging, preparing and accurate data delivering to business users. DataLabs is a Qlik Certified Partner and is committed to meet your data management challenges. You can request here.

Previous #fridaypost “Corporate data knowledge is a key for a business success”

Last time we defined current data architects’ tasks: metric clarity ensuring, information sources identifying and managing, consistency ensuring, maintaining relationship among terms,

How to solve them?

The main tool for these tasks solving is knowledge about corporate data landscape, information consuming and accessing processes, «data mechanics» that can be used to develop the convenient report and analytic environment.

There are 3 elements of corporate information knowledge governance:

intelligent data collecting;
data organization and enhancement;
high usability.

All these 3 elements can be possible with data governance technologies and methods as:

Data storage environment research across the enterprise to identify and inventory data assets;
Identified data assets profiling to collect structured metadata, data quality estimation, semantic tags identification, potential problems definition;
Documenting object metadata including data owner information and aspects its origin;
Data elements classification by every structured element of data asset estimation and attaching to the appropriate business term;
Indexing and providing of the searchable semantic registry of business glossary terms and elements;
Quality and usability audit of every data asset element. It provides a possibility to rapidly create reports of the actual performance measures for data quality compliance.

Such methods usage allows to create a corporate data catalog that provides different benefits with data consumers. This catalog is a repository for data assets inventory. It also serves as an enterprise resource and with its help data architects and consumers can share knowledge. It documents the high-level object metadata, identifies data elements and maps them to the semantic business glossary. This information can be used into an intelligent search that allows consumers to browse data assets, define more suitable data sets for reporting and analytics for every business scenario.

Effective enterprise data management with Qlik Catalog

The modern Data Catalog helps to achieve maximum value for the business

Previous #fridaypost “Corporate data knowledge is a key for a business success”

Data Catalog – clarity, transparency and usability

Previous #fridaypost «Main BI drivers»