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

CIO Business Intelligence

Imagine generating complex narratives from data visualizations or using conversational BI tools that respond to your queries in real time. Tableau, Qlik and Power BI can handle interactive dashboards and visualizations. Even basic predictive modeling can be done with lightweight machine learning in Python or R.

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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. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2) Data Discovery/Visualization. Data exploded and became big.

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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

For example, if I am searching for customer sales numbers, different datasets may label that “ sales ”, or “ revenue ”, or “ customer_sales ”, or “ Cust_sales ”, or any number of other such unique identifiers. What a nightmare that would be! But what a dream the semantic layer becomes!

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Automating the Automators: Shift Change in the Robot Factory

O'Reilly on Data

Building Models. A common task for a data scientist is to build a predictive model. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

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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. Now, BA can help you understand why did sales spike specifically in New York.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. That is precious insight for the sales team who can look into the data in real-time and understand what the leverages beneath it are. The results? 6) Smart and faster reporting.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Moreover, advanced metrics like Percentage Regional Sales Growth can provide nuanced insights into business performance. Data in Use pertains explicitly to how data is actively employed in business intelligence tools, predictive models, visualization platforms, and even during export or reverse ETL processes.

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