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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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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.

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Splunk Tutorial For Beginners: It’s Application & Features

Pickl AI

It initiates the collection, indexing, and analysis of machine-generated data in real-time. The tool is loaded with features, thus making it a popular choice for businesses. It helps harness the power of big data and turn it into actionable intelligence. Additionally, it also supports a host of data formats.

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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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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics. Have you worked with cloud-based data platforms like AWS, Google Cloud, or Azure?