MARKET IMPACT SURVEY - COVID-19 & LOOMING RECESSION
Timely market intelligence is paramount in these uncertain times!
We launched an impact survey to update this project with timely insights during 2020. Update frequency will depend upon evolving market conditions and executive opinions. Our participants are executives driving strategy, marketing, sales and product management at competitive companies worldwide. All updates during the rest of the year are complimentary to clients!
The global market for Data Catalog is projected to reach US$1. 0 billion by 2025, driven by years of digital transformation which is currently reaching maturity in most industries and the ensuing massive accumulated value of digital assets and the need now to efficiently manage these data assets. Data unification and data collaboration are the foundation of successful data-driven strategies and therefore require metadata management and cataloging. Data catalog is an inventory of data assets that provide meaning and context needed to extract business insights from data. Data catalog enables easy discovery of corporate metadata; automatic harvesting & classification of data; improves usability of data; & aids in easy management of data quality issues. A data catalog is offered to data users as a reference application, being the first stop for a self-service data discovery task. The catalogs enable varied users that include data analysts, business analysts, data stewards, and data scientists to easily find, comprehend, explore, collaborate and trust data for performing self-service analytics through a single reference source within a data lake or data warehouse via annotations that improve data using context. A data catalog comprises a simple means of accessing data that is required by data consumers for performing their tasks. The tool enables in managing data as well as assists in data quality by enabling users to work collectively from a single self-service environment.
Data catalogs encompass an array of attributes, combining metadata with datasets that are used for analysis; wherein the metadata is responsible for illustrating standard database objects, including schema, tables, and queries that are stored in data lakes, data warehouses or some such systems. This could be improved with sample projects and annotations developed in analytic or business intelligence (BI) applications; as well as shared by data users via the catalog. A data catalog, in the physical form, is an on-premise or cloud-based server that enables automatic indexing of data systems, providing a database for the assets that could be approached through a single source. A data catalog crawls business intelligence systems and databases for providing a single reference point pertaining to enterprise data. Data catalogs offer major stakeholders with context to locate and comprehend data; as well as automate management of metadata, thereby making the same collaborative. Consequently, data catalogs could be used for extended purposes, enabling stakeholders to understand data, as well as act on and organize the same. Resultantly, the facet in regards to data collaboration and automation holds extreme significance. A few data catalogs depend on machine learning for providing extra behavioral context in regards to the method in which the data is being utilized. Analysing logs enables to make certain assumptions in regards to the quality or usefulness of the data approached by the data catalog. A user is able to figure out the frequency of a specific schema or table being accessed; their recent use and time; and the user who accessed the data. Consequently, a data catalog incorporates extra context that merely the data would not have been able to determine. Additionally, a data catalog, rather than requiring to identify a connection ring or the path for connecting to data source, offers a purpose-built client application for consuming data; as well as utilize specific conventions from commonly used online consumer catalogs, including Pinterest, Wikipedia, Spotify, and Yelp. Users browse, search, or surface recommendations for finding data, instead of typing vague and unclear demands.