How to modernize data analytics architecture for the cloud?

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More and more companies are implementing processes to modernize their data analysis architecture in the cloud because, by managing it effectively, they can reach smarter decisions for the business.

Challenges of data analytics architecture
Today, there is an explosion of data from a vast number of sources, as well as a huge demand to consume it. However, traditional methods are not able to effectively respond to this demand.

This is the conclusion reached by the report “ Modernizing your data architecture to unlock business value ”, carried out by TDWI Pulse, which revealed that 57% of the companies surveyed need several weeks to add new data to BI and analytics platforms.

Furthermore, 55% consider using data from mainframe or legacy applications to be the most complex and a significant percentage, 43%, have difficulties using data from local ERP systems, such as SAP and Oracle.

As if this were not enough, it is not only about analyzing and governing internal data , but there is much more data available to organizations outside of it, which becomes essential to attend to.

Data thrives in a variety of heterogeneous systems that contain iceland phone number lead valuable information to be leveraged – linking these systems together could prove invaluable to organisational growth. Current limitations tied to the need for agile data acquisition have significant business impact .

TDWI's report states that enterprises need an architecture that not only enables users to generate insights on their own, but also adapts to an unpredictable or constantly changing data landscape .

In response to this, emphasis must be placed on the ability to keep data moving and analyze the most recent data in order to react in real time to what is happening in the business.

To achieve this, companies must build a cloud data analytics architecture .

Qlik modernizes data analytics architecture for the cloud
Qlik is a cloud-first company and AWS partner with technical expertise and proven success in automating and accelerating cloud migration.

Qlik unlocks business value from data by aligning with AWS. How does it do it?

Automating data delivery to multiple AWS services, from storage and data warehouses to streaming systems.
Improving access to enterprise data through Qlik Data Integration, the Change Data Capture (CDC) tool, which enables transactional data to be moved to the AWS Cloud in a consistent manner.
Integrating cloud data lakes and warehouses.
Handling real-time data use cases.
Automating data flows from heterogeneous sources, including mainframe and SAP systems.
Establishing a unified metadata repository with Qlik Catalog, allowing the data engineer to verify data quality; the data steward to label, protect and mask sensitive data; and the business user to find and publish data to the BI tool of their choice.
Offering data analytics independently of Qlik data integration, but empowering its use, making data more accessible with self-service capabilities.
Driving better and faster insights, while maintaining data security and control.
Modernizing your data analytics architecture for the cloud improves performance, agility, and data security. With Qlik, it's possible.