For most businesses out there, I suspect that anything more complex than Fivetran + Snowflake + dbt Labs + whatever BI tools might be an over-engineered Data Analytics system. Am I missing something? By the way - in terms of BI tools - at Data Captains we found that companies like Preset offer a great balance between ease of use, flexibility, costs, and support.
Mattia Ciollaro’s Post
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We talk so much about the effort it takes to clean data, but what does that even mean? It's so true that there are only a few ways to structure data in a "tidy" manner and infinitely many ways to make it messy.
What do we mean when we say "Tableau prefers tidy data?" In this latest installment of the "Mental Models" series, Actionaut Keith Helfrich explores the idea that “tidy data” isn’t just about “cleanliness” of data; it is actually a format, a standardized structure, that is critical to the process of extracting meaning from data. https://lnkd.in/gQ9BGuYs
Mental Model #2: Tableau Prefers Tidy Data
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If you’ve been here for awhile, you’re probably used to seeing exclusively data analytics and machine learning content, BUT Qlik is so much more than that! We, combined with our recent acquisition of Talend are a complete, end-to-end solution. I’m here to help you make the most of your data, from ingestion to machine learning - are YOU ready?! #dataintegration #analytics #machinelearning
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What do we mean when we say "Tableau prefers tidy data?" In this latest installment of the "Mental Models" series, Actionaut Keith Helfrich explores the idea that “tidy data” isn’t just about “cleanliness” of data; it is actually a format, a standardized structure, that is critical to the process of extracting meaning from data. https://lnkd.in/gQ9BGuYs
Mental Model #2: Tableau Prefers Tidy Data
https://www.youtube.com/
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Do you conduct or use #analytics in your organization? Of course right!! Who doesn’t? Feel free to learn over the NOON eastern lunch time how to design your own analytics pipeline in order to make more impactful decisions and increase your goals! #etl #bigquery #pipeline #webinar
Data Engineer's Lunch 106: Designing an analytics pipeline with BigQuery and dbt: a walkthrough
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🔍 Ranking is an essential part of analytics. It's common to ask questions like: Which are my top-performing accounts? How much is the monthly trend of the top-performing products different from all other products? Which are the top-performing products in each country? While these questions seem similar, each one requires a different type of query to visualize effectively. 📊 Check out the video below to see how easy it is to answer all these questions in Astrato. The video also highlights another crucial aspect: push-down SQL, featuring easy-to-read and debug SQL queries. 🚀 If you want to see more of Astrato Analytics's magic, join us at the Databricks Data+AI Summit! #DataAnalytics #Ranking #Astrato #SQL #DataVisualization #Databricks
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Register Now : https://cutt.ly/qwJ515Yr Ready to revolutionize your data skills? Discover Knime's No-Code approach in our Self-Paced Course and elevate your career effortlessly! Enroll now to start your data science journey today. #dicecamp #diceanalytics #datascience #knime #nocode #besttraininginstitute #selfpacedlearning
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An introduction to understand how you can develop a data pipeline by using dbt and snowflake 👇 https://lnkd.in/eRmYFJpv
Using dbt And Snowflake To Develop And Deploy Analytics Code | LAB
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Pro-tip for newer data teams: Your data stack should be determined by your end goal, not what you think is cool or fun to use. For example, if your goal is to train and serve a real time machine learning model, Snowflake might not be the best choice for you. Databricks and Tecton are likely a better fit. Really, the only non-negotiables for most companies are: → A loader → A destination for the data → A Business Intelligence tool … and pretty much everything else gets classified as “nice to have”. My point is that you can’t have “Data Stack FOMO”. Every company has different goals, and that means your data stack is likely going to be different too. If a tool will help you make high-quality, relevant decisions about your business, add it. If not, it can wait.
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TTT Certified || Senior Training Consultant - Ops || Corporate Trainer - Ops || IT Services || Ed-tech
Heading towards the Summit! Driven by the pursuit of Summit! Anticipating a wealth of kipi.bi stakeholders, as well as exciting Snowflake updates. Let's spotlight the advancement in #AdvancedAnalytics!
CHASING SUMMIT!!! ❄️🏔️ Here we are, on the road again, chasing Summit! #snowflakesummit Looking forward to an overload of kipi.bi Customers, Partners and Snowflake announcements. Let the ‘Advance’ in #AdvancedAnalytics be known! Can’t wait to meet our allies from Matillion Fivetran dbt Labs Sigma Computing Hevo Data Tableau Dataiku and of course Snowflake. Cheers!
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7 facts about DAX authoring that everyone should know ✅ Row context iterates on a table ✅ Filter context filters the data model ✅ Variables can only be used locally ✅ A poor data model will generate unexpected results ✅ No date table = Unreliable Time Intelligence calculations ✅ Virtual tables are the lifeblood of higher-level calculations ✅ You will go bald trying to return a scalar with a table function 😂 Happy Friday! P.S. What else would you add? #powerbi #dax #coding #businessintelligence #data #dataanalytics
Venture Capital | Startups | Data Science | Strategy
2wA data management platform for data integration, ETL/ELT, data governance, and offers a solution for data quality? Maybe a unified platform like Talend?