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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

The solution consists of the following interfaces: IoT or mobile application – A mobile application or an Internet of Things (IoT) device allows the tracking of a company vehicle while it is in use and transmits its current location securely to the data ingestion layer in AWS.

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Smart Factories: Artificial Intelligence and Automation for Reduced OPEX in Manufacturing

DataRobot Blog

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). This is currently a widespread strategy across the industry where we are seeing companies move from reactive to predictive inventory management and capacity planning. Factory Monitoring?—?

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Migrate from Amazon Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics Studio

AWS Big Data

Kinesis Data Analytics for Apache Flink In our example, we perform the following actions on the streaming data: Connect to an Amazon Kinesis Data Streams data stream. View the stream data. Transform and enrich the data. Manipulate the data with Python. Navigate to the AWS IoT Core console.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

In this article, we’ll dig into what data modeling is, provide some best practices for setting up your data model, and walk through a handy way of thinking about data modeling that you can use when building your own. Building the right data model is an important part of your data strategy. Discover why.

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Agent Swarms – an evolutionary leap in intelligent automation

CIO Business Intelligence

The Agent Swarm evolution has been propelled by advancements in computing, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). This flexibility renders agent assemblies an essential element in contemporary automation strategies. The call to action is as clear as it is compelling.

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