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Big Data vs Data Warehouse

Marktechpost

With their own unique architecture, capabilities, and optimum use cases, data warehouses and big data systems are two popular solutions. The differences between data warehouses and big data have been discussed in this article, along with their functions, areas of strength, and considerations for businesses.

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Tableau vs Power BI: Which is The Better Business Intelligence Tool in 2024?

Pickl AI

Introduction Business Intelligence (BI) tools are crucial in today’s data-driven decision-making landscape. They empower organisations to unlock valuable insights from complex data. Tableau and Power BI are leading BI tools that help businesses visualise and interpret data effectively. billion in 2023.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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Popular Data Transformation Tools: Importance and Best Practices

Pickl AI

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations.

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deepsense.ai at SQLDay

deepsense.ai

SQLDay, one of the biggest Microsoft Data Platform conferences in Europe, is set to host an insightful presentation on GPT in data analysis by Maksymilian Operlejn, Data Scientist at deepsense.ai. The presentation entitled “GPT in data analysis – will AI replace us?”

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Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. And you should have experience working with big data platforms such as Hadoop or Apache Spark.