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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

This article reflects some of what Ive learned. They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. Tableau, Qlik and Power BI can handle interactive dashboards and visualizations.

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The quest for high-quality data

O'Reilly on Data

Moreover, the domain knowledge, which often is not encoded in the data (nor fully documented), is an integral part of this data (see this article from Forbes). See this article on data integration status for details. business and quality rules, policies, statistical signals in the data, etc.).

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. We detailed the benefits and costs of good or bad quality data in our previous article on data quality management , where you can read the five important pillars to follow. Data exploded and became big.

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Managing risk in machine learning

O'Reilly on Data

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. As we deploy ML in many real-world contexts, optimizing statistical or business metics alone will not suffice. David Talby summarized some of these key challenges in a recent post : Your models may start degrading in accuracy.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

For example, if you enjoy computer science, programming, and data but are too extroverted to program all day long, you could work in a more human-oriented area of intelligence for business, perhaps involving more face-to-face interactions than most programmers would encounter on the job. BI engineer. Here we will name 3 of the top ones.

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What Is The Difference Between Business Intelligence And Analytics?

datapine

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. But let’s see in more detail what experts say and how can we connect and differentiate the both.

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Why Data Driven Decision Making is Your Path To Business Success

datapine

From these developments, data science was born (or at least, it evolved in a huge way) – a discipline where hacking skills and statistics meet niche expertise. Quantitative data analysis focuses on numbers and statistics. Qualitative data analysis is based on observation rather than measurement.