Data catalog is an inventory of the assets of the data in the organization. It employs the metadata to assist the organization that manage their data. It is also essential for the data professionals that gather, access, enrich and organize the metadata to assist the data discovery and the governance. Many objects store the databases and the data warehouse which are provided today.
The data catalog market was valued at US$ 633.09 Mn in 2021 and is forecast to reach a value of US$ 4397.75 Mn by 2030 at a CAGR of 24.3% between 2022 and 2030.
North America held a dominant position in the Global Data Catalog Market Share in 2021
Figure 1: Global Data Catalog Market Value (US$ Bn) Analysis and Forecast, 2017 - 2030
North America held dominant position in the Global Data Catalog Market in 2021, accounting for 29.30% share in terms of volume.
Figure 2: Global Data Catalog Market Share (%), By Region, 2021
In March 2021, TIBCO software Inc. declared the involvement of Apache Pulsar and Apache Kafka as a cloud service in TIBCO Cloud messaging. With this a business can add a real time data efficiency into the deployment of the on-premises applications for the better responsiveness without the requirement to purchase the additional software or hardware when they are linked to Pulsar and Kafka data to the hybrid surroundings.
In January 2021, Tibco Software Inc. declared the adoption of the information builders Inc., a supplier of the services and the facilities in the fields of business intelligence, data integration and the solutions of the data quality. The acquirement will leverage the increase of ibi’s data management and the analytics abilities to the developed TIBCO connected intelligence platform which comprises of the TIBO’s data catalog as well.
|Base Year:||2021||Market Size in 2021:||US$ 633.09 Mn|
|Historical Data for:||2017 to 2020||Forecast Period:||2022 to 2030|
|Forecast Period 2022 to 2030 CAGR:||24.3%||2030 Value Projection:||US$ 4397.75 Mn|
IBM Corporation, TIBCO Software Inc., Altair Engineering Inc., Microsoft Corporation, Oracle Corporation, Collibra NV, SAP SE, Tamr Inc., Alteryx Inc., Zaloni Inc., Hitachi Vantara LLC, Informatica Inc., Amazon Web Services Inc. and Alation Inc.
|Restraints & Challenges:||
With the increase of the big data and the processes and the tools associated to the utilization and managing of the large data sets, organizations to identify the value of data as a critical business asset for the identification of the trends, patterns and choices is anticipated to drive the customer experience and then fuel the growth of the global data catalog market.
The problems is that the consumers often cannot find or achieve the data they require to perform the desired analytics. The data is generally buried in various systems or the siloed in the departments over the organizations. The data catalog industry has seen a surge in the tool of self-service analytics.
Enterprises are faced with the problems pertaining to unstructured data that leads in the difficulties in the execution of the catalog solutions. A data scientist who is willing to access the enterprise data for the modelling or to deliver the insights for the analytics teams is faced with the difficulties to dive into the depths of the undefined data sets from various sources.
Additionally, several enterprises that spend in the storage of the data warehouse or the legacy data end up in the silos that are turned into the unutilized data for the enduring period where the repositories of the undefined set of data from various multiples disparate sources such as the datasets which tend to be difficult for deployment for the data catalogs.
Data catalog is a basic step for any modern data preparation initiative. DataOps teams, comprise of the data scientists, the data engineers and the data analysts are progressively using the Artificial Intelligence powered catalog to easily observe their data within the petabytes of the data that is residing in the deployment and the cloud data lakes. Organizations are struggling to the inventory distributed data assets to fuel the data monetarization and also conform to rules.
Automated ML based discovery procedure can transform that is associated to the data assets into the intelligent recommendations that may be similar to users, decreasing duplicate datasets form being created for similar projects. Further development of data catalogs needs to be directed ate the integrating with a vast variety of the applications.
Market Key Takeaways/Trends:
The APIs need to assist the integration of the catalog with a customer’s personal usage and applications. The various forms of the metadata standards utilized over the libraries, achievers and the museums make metadata interoperability extremely challenging. Publishing metadata as the RDF permits the sharing and re-usage of the metadata over the institutions.
The rising partnership and the decreasing record duplications. This can Internet protocols with much time span to focus on the creation of the much details description for the local resources. The challenges that are initially inhibited building a data lake were keeping track of all of the raw assets as they are loaded on the data lake.
Major companies involved in the growth of the global data catalog market are IBM Corporation, TIBCO Software Inc., Altair Engineering Inc., Microsoft Corporation, Oracle Corporation, Collibra NV, SAP SE, Tamr Inc., Alteryx Inc., Zaloni Inc., Hitachi Vantara LLC, Informatica Inc., Amazon Web Services Inc. and Alation Inc.
Not only the data accessing is being a challenge however, the data governance has being with a challenge and it is very critical to understand the type of data that one has, who is moving it, what it is being utilized for and how it requires to be protected. However, to ignore too many layers and the wrappers around the data.
The data catalog displays the inventory of all the accessible data in the organization by maintaining the metadata that it describes. Leading to that the sellers in the market are announcing the latest data catalogs that is powered by the technologies. Similarly as the google indexes the internet.
Not every tool assists the huge amount of catalog metadata. The tools when loaded with the humongous amount of the metadata, breakdown due to the performance issue and few tools can only accommodate a restricted amount of data on the data assets.
The execution of the data catalogs assists the improvement of the supply chains by decreasing the data isolation in between the data source to its analysis. The data permits the user from various backgrounds within an industry to annotate the data for the future utilization.
Key features of the study: