Remove Business Intelligence Remove Data Analysis Remove Internet of Things
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How IoT Can Be Connected to Business Intelligence

Smart Data Collective

IoT solutions as well as Business Intelligence tools are widely used by companies all over the world to improve their processes. First of all, you need to define what data should be collected from your IoT devices, processed, and visualized. Proceed to data analysis. But what if we combine these technologies?

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Get Ready For These Six 2020 Business Intelligence Trends

Smart Data Collective

More and more often, businesses are using data to drive their decisions — which makes cutting-edge analytics and business intelligence strategies one of the best advantages a company can have. Here are the six trends you should be aware of that will reshape business intelligence in 2020 and throughout the new decade.

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Utilize smart technologies to make smart investments

Dataconomy

In the modern era of data-driven decision-making, business intelligence projects have become the cornerstone for organizations aiming to harness their data for strategic insights. So which business intelligence projects can you trust in your next adventure? But this diversity often leads to sound pollution.

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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

By using this method, you may speed up the process of defining data structures, schema, and transformations while scaling to any size of data. Through data crawling, cataloguing, and indexing, they also enable you to know what data is in the lake. References: Data lake vs data warehouse

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Exploring the fundamentals of online transaction processing databases

Dataconomy

Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications.

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Navigating the 2024 Data Analyst career growth landscape

Pickl AI

Summary: The blog delves into the 2024 Data Analyst career landscape, focusing on critical skills like Data Visualisation and statistical analysis. It identifies emerging roles, such as AI Ethicist and Healthcare Data Analyst, reflecting the diverse applications of Data Analysis.

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Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Pickl AI

On the other hand, a Data Warehouse is a structured storage system designed for efficient querying and analysis. It involves the extraction, transformation, and loading (ETL) process to organize data for business intelligence purposes. It often serves as a source for Data Warehouses.