Remove Analytics Remove Cost-Benefit Remove Dashboards Remove Data Warehouse
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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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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. As figure 2 summarizes, the data team ingests data from hundreds of internal and third-party sources.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

The solution should be scalable, cost-efficient, and straightforward to adopt and operate. Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. version cluster.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

In today’s dynamic business environment, gaining comprehensive visibility into financial data is crucial for making informed decisions. This is where the significance of a financial dashboard shines through. What is A Financial Dashboard? You can download FineReport for free and have a try! Free Download of FineReport 1.

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Choosing the right Data Warehouse SQL Engine: Apache Hive LLAP vs Apache Impala

Cloudera

Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data.

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Don’t Blink: You’ll Miss Something Amazing!

Cloudera

We can also increase effectiveness of preventative maintenance — or move to predictive maintenance — of equipment, reducing the cost of downtime without wasting any value from healthy equipment. With this, we can reduce customer churn and overall network operational costs.

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

AWS Big Data

Credit: Phil Goldstein Jerry Wang, Peloton’s Director of Data Engineering (left), and Evy Kho, Peloton’s Manager of Subscription Analytics, discuss how the company has benefited from using Amazon Redshift. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.