Five Things to Consider When Choosing a Data Catalog

February 20, 2019

The self-service data analytic journey often begins with choosing a data catalog. Before businesses can make the most of their corporate data, analysts need the ability to find and use trusted data, share insights about that data, crowdsource quality attributes and have recommendations presented that relate to data sources that have been discovered.Organizations face growing challenges. The volume of data is exploding and coming from various sources structured, unstructured data, IoT, the cloud, etc. thus, driving the growth of the business analytics market. But not all data catalog solutions are the same. The four distinct data catalog types include:Data Lake Catalog works well if all your data is in a single data lake.Data Warehouse Catalog is more ideal for legacy data warehouses and data management.Cloud Catalog for vendors who offer cloud compute and storage, predisposes you have all your data in their cloud.Enterprise Data Catalog does not discriminate where your data is, what structure it is in or any other restriction, but establishes a virtual data layer to bring all your catalog data into one centralized place.

Spotlight

Arundo Analytics

With offices in Oslo, Houston and Silicon Valley, Arundo Analytics provides cloud-based and edge-enabled software for the deployment and management of enterprise-scale industrial data science solutions. Arundo's software allows industrial companies and other organizations to increase revenue, reduce costs and mitigate risks through machine learning and other analytical solutions that connect industrial data to advanced models and connect model insights to business decisions.

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