Remove Data Analytics Remove Data Warehouse Remove Finance
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Bringing Financial Services Business Use Cases to Life: Leveraging Data Analytics, ML/AI, and Gen AI

Cloudera

Key use cases include customer journey/customer 360, regulatory compliance, financial crime prevention, risk management, market risk, credit risk, liquidity risk, operational risk, systemic risk, climate risk, intraday risk management, finance, integrated risk and finance view, treasury management, advanced analytics, and emerging technology.

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Sun King uses Amazon Redshift data sharing to accelerate data analytics and improve user experience

AWS Big Data

Sun King designs, distributes, installs, and finances solar home energy products for people currently living without reliable energy access. Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale.

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The New Normal for FP&A: Data Analytics

Jedox

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new. Limited internal resources.

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How to implement access control and auditing on Amazon Redshift using Immuta

AWS Big Data

Data security is one of the key functions in managing a data warehouse. With Immuta integration with Amazon Redshift , user and data security operations are managed using an intuitive user interface. This blog post describes how to set up the integration, access control, governance, and user and data policies.

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Peloton embraces Amazon Redshift to unlock the power of data during changing times

AWS Big Data

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. This analytics function is so crucial to product success that the data team often reports directly into sales and marketing. Figure 3: The vast and varied types of analytics required during the launch phase.

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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

If your company is using Microsoft Dynamics AX, you’ll be aware of the company’s shift to Microsoft Dynamics 365 Finance and Supply Chain Management (D365 F&SCM). OLAP reporting has traditionally relied on a data warehouse. Unfortunately, Microsoft is not providing that kind of data warehouse solution out of the box.