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Analytics

Why You Should Move From Management Reporter to Jet Reports

Much like Apple people tend to be all Apple, all the time, Microsoft Dynamics ERP users tend to prefer Microsoft products for all their computing needs. It’s not hard to understand why. Using products from the same ecosystem prevents compatibility issues and saves time in learning multiple systems.

Top 10 Data Extraction Tools for 2023

A data extraction tool can help improve the accuracy of data by automating the extraction process and reducing the risk of human error. This can lead to more reliable and consistent data that can be used to make better business decisions. Moreover, data extraction tools can help you increase productivity and improve the quality of your data as they automate the process of retrieving data from multiple sources.

Building a Data-Centric Platform for Generative AI and LLMs at Snowflake

Generative AI and large language models (LLMs) are revolutionizing many aspects of both developer and non-coder productivity with automation of repetitive tasks and fast generation of insights from large amounts of data. Snowflake users are already taking advantage of LLMs to build really cool apps with integrations to web-hosted LLM APIs using external functions, and using Streamlit as an interactive front end for LLM-powered apps such as AI plagiarism detection, AI assistant, and MathGPT.

Discovering Data Monetization Opportunities in Financial Services

Data has become an essential driver for new monetization initiatives in the financial services industry. With the vast amount of data collected from customers, transactions, and market movements, among other sources, this abundance offers tremendous potential for financial institutions to extract valuable insights that can inform business decisions, improve customer service, and create new revenue streams.

Data Mesh vs. Data Fabric

In today’s data-driven world, businesses must deal with complex challenges related to managing, integrating, and properly using massive amounts of data housed in multiple locations. Organizations that unlock the right data architectural approach empower themselves with much better decision-making and strategic insights. Two popular approaches — data mesh and data fabric — have surfaced as prominent and innovative solutions for handling data at scale.