Remove Data Warehouse Remove Operational Reporting Remove Predictive Modeling
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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

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What is a Data Pipeline?

Jet Global

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

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The Benefits, Challenges and Risks of Predictive Analytics for Your Application

Jet Global

Data-Driven Decision Making: Embedded predictive analytics empowers the development team to make informed decisions based on data insights. By integrating predictive models directly into the application, developers can provide real-time recommendations, forecasts, or insights to end-users.

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Transformative Change: How AI is Impacting the Manufacturing Industry

Jet Global

Demand Forecasting: Machine learning analyzes sales data to predict future demand, leading to better inventory management and resource allocation. Risk Management: AI-powered anomaly detection and predictive modeling identify potential supply chain disruptions, allowing for proactive risk management.

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What Is Embedded Analytics?

Jet Global

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. It is organized to create a top-down model that is used for analysis and reporting.

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2024 Embedded Analytics Round-Up

Jet Global

This enables organizations to build and deploy conversational BI agents, predictive models, and real-time data insights seamlessly, empowering users with personalized and actionable intelligence at scale.

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How to Handle Missing Data Values While Data Cleaning

Jet Global

The column to predict here is the Salary, using other columns in the dataset. If there are missing values in the input columns, we must handle those conditions when creating the predictive model.