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Active Data Warehousing Market Outlook and Opportunities in Grooming Regions : Edition 2019-2024

Active Data Warehousing Market

Global Active Data Warehousing Market – Growth, Trends, And Forecast (2019 – 2024)

Active data warehouse is a repository of any form of captured transactional data so that they can be used for the purpose of finding trends and patterns to be used for future decision making. An active data warehouse has a feature that can integrate data changes while maintaining batch or scheduled cycle refreshes.

The global active data warehousing market was valued at USD 5.67 billion in 2018 and is expected to reach a value of USD 10.75 billion by 2024, at a CAGR of 11.17% over the forecast period (2019-2024).

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Top Companies in the Global Active Data Warehousing Market:

ORACLE CORPORATION, HEWLETT PACKARD ENTERPRISE CO, MICROSOFT CORPORATION, SAP SE, AMAZON WEB SERVICES INC, Tresure Data Inc., Cloudera Inc., Snowflake Computing Inc., Pivotal Software, Inc., Huawei Technologies Co. Ltd, Teradata Corporation, Kognitio Ltd, IBM Corporation

Market Overview:

In recent years, due to rising concerns on data manageability and increasing complexity, data warehousing has attracted significant interest in real-life applications, especially in finance, business, healthcare, and other industries.
The increased need for quick business decisions and growing competition have augmented the importance of business intelligence and real-time data analytics dramatically, which are dependent on real-time date warehousing solutions.
The increasing dependency on big data analytics and business intelligence solutions has predominantly increased the need for more sophisticated data warehousing developers and administrators.

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Key Market Trends:

Hybrid Deployment Expected to Witness Rapid Growth

Although most companies benefit significantly by deploying a cloud-based data warehouse as it is cost-effective, quick to set up, and instantly scalable, companies that require total control, flexibility, accessibility, and predictability might find that an on-premise solution is a better fit for their needs.
If organizations are unsure of choosing the best model fit for their needs, they opt for a hybrid approach, storing their data in an on-premise data center and using the cloud for data processing and analytics. Alternatively, they can store the data in a cloud data warehouse and perform analytics on-premise as well.
The suitable solution for this would be to implement a hybrid approach, where the internal systems can be protected by secret server on-premise and cloud services can be protected on the secret server cloud.
Another compelling reason behind adopting the hybrid model is that investment organizations have already settled into on-premise hardware and software. Software and hardware infrastructure is expensive, and organizations may be unwilling to abandon those capital expenditures, just to move to the cloud. Rather than migrating to the cloud infrastructure entirely, the best possible alternative will be to inherit the hybrid model and make the maximum use of both models.

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