Business Intelligence Data Analysis Internet of Things 
Smart Data Collective
NOVEMBER 25, 2019
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.
Smart Data Collective
JANUARY 10, 2023
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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Dataconomy
AUGUST 24, 2023
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.
Data Science Dojo
JANUARY 12, 2023
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
Dataconomy
APRIL 27, 2023
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.
Pickl AI
JANUARY 16, 2024
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.
Pickl AI
NOVEMBER 15, 2023
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.
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