Accelerating Your Analytics Journey: Part One

Data. According to Merriam Webster, data is “information in digital form that can be transmitted or processed.” Sounds simple. Sounds like something that’s everywhere. However, smart, influential business leaders will tell you data is important. It’s powerful. It’s a key…

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How to Deploy Machine Learning on Google Cloud Platform

Editor’s Note: Because our bloggers have lots of useful tips, every now and then we update and bring forward a popular post from the past. Today’s post was originally published on August 15, 2019. In this post, I’ll describe a…

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Dipping Your Toes Into Building an Analytics Platform on Google Cloud Platform

“We have many disparate data sources and we’re having a hard time getting a global view of all our data across our organization.” “Our data is currently all in <enter data warehouse name here> and we want to migrate it…

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Global Analytics with Azure Cosmos Db and Synapse Analytics – SQL On The Edge Episode 21

A few months ago, Microsoft revealed that they were looking into adding a capability of querying Cosmos Db data through Spark and this immediately got me thinking into the new scenarios this would enable. The most ambitious is the capability…

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The Shift in Top Big Data Analytics Trends for 2020

The Shift in Top Big Data Analytics Trends as We Enter 2020

In 2019, we forecasted and highlighted the top trends in big data analytics. Today we will be revisiting this topic to explore how the trends have progressed as time has evolved. As we dive deeper into the digital age, the…

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Making a business case for Machine Learning

The first step to kick off a Machine Learning (ML) project is to have a written proposition for the business problem, and second, to frame the ML problem. Before even discussing an ML method, it is necessary first to understand…

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An overview of best practices for implementing ML systems – Part 1

In this series of blog posts, we will recommend some best practices identified from our own failures and successes throughout our time implementing machine learning (ML) systems. We won’t discuss ML techniques here, but instead, provide an upper-level overview of…

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An Oracle-based approach to the “taxi fare” prediction problem – episode 2

This is the second part of the series on the Taxi Fare prediction problem from an Oracle perspective. You can read Episode 1 here. In this Episode, I will put our model to work. That is, I will show several…

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Analyzing BigQuery via Excel and Google Sheets

Both MS Excel and Google Sheets offer ways to connect directly to BQ data, to run queries, to pull data back to Excel/Sheets and allow further analysis via options such as pivot tables, charts and drilling up/down. MS Excel The…

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Azure Data Lake basics for the SQL Server DBA / developer and… for everyone!

The basics If you’re a Microsoft SQL Server DBA or developer and have not been introduced to the Microsoft Azure Data Lake and would like to understand what it’s all about and how to get started, this article is for YOU….

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