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Sisense’s Q2 Release: A Modern Data Experience Across the Analytics Continuum

Sisense

In-Warehouse Data Prep provides builders with the advanced functionality they need to rapidly transform and optimize raw data creating materialized views on cloud data warehouses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses. Additional capabilities.

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The Data Journey: From Raw Data to Insights

Sisense

Every organization generates and gathers data, both internally and from external sources. The data takes many formats and covers all areas of the organization’s business (sales, marketing, payroll, production, logistics, etc.) External data sources include partners, customers, potential leads, etc. Connect tables.

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Common Business Intelligence Challenges Facing Entrepreneurs

datapine

Armed with BI-based prowess, these organizations are a testament to the benefits of using online data analysis to enhance your organization’s processes and strategies. In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources.

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Simplify Metrics on Apache Druid With Rill Data and Cloudera

Cloudera

Co-author: Mike Godwin, Head of Marketing, Rill Data. Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Cloudera Data Warehouse). Efficient batch data processing.

Metrics 87
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13 power tips for Microsoft Power BI

CIO Business Intelligence

Visualize all the services you use Power BI has hundreds of content packs, templates, and integrations for hundreds of data services, apps, and services — and not just Microsoft ones such as Dynamics 365 and SQL Server. Integrate with Office If your users prefer to slice and dice with Pivot tables, Power BI data can also be used in Excel.

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How OLAP and AI can enable better business

IBM Big Data Hub

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 57
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Business Intelligence vs. Reporting: Finding Your Bread and Butter

Jet Global

Business Intelligence Infrastructure: The overall concept of business intelligence platforms is that they take that raw, two-dimensional, live data, parse it down to only the relevant, useable pieces and then structure it, subjectize it, and finally, dimensionalize it, so the data is completely optimized for analysis.