Will we ever see a world where there are no longer gasoline-fueled cars on the road? Of course!  Why spend money on gas and pollute the planet when you can save mother earth and spend less? Ironically, gasoline as energy will become extinct, just like the dinosaurs that produced it. Will we ever see a world where users won’t care which database system their data came from, but instead query as quickly as doing a browser search over the internet? Of course!  Why spend time and money moving data to a single platform to have a single version of the truth when the truth can reside across many data sources?  Ironically, users with no technical background can now join data across platforms thousands of times faster than today’s best data scientists. Virtualization is the ability to join data no matter where it resides without any technical expertise, and it is as inevitable in data as electricity is to cars!

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Data virtualization allows users to move or join data across database platforms with no technical experience.  Why spend millions moving data when your users can join data across platforms? Data virtualization is the best way to see your data in action, and thus, it has become an important tool for various business lines to get the insights their teams need. Join us on Thursday, January 21st, at 10:00 PST (1:00 EST) for a 20-minute webinar to hear from Yellowbrick, along with two solution partners, Nexus and Soterosoft, to learn how to build a virtualization roadmap.

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In July 1799, Rosetta Stone, discovered during Napoleon Bonaparte’s campaign through Egypt, became one of the British Museum’s most famous objects. But what is it, and why is it important to computing?

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Over the next two days, I am teaching Snowflake SQL remotely to Ivy League students. I have taught close to 1,000 SQL classes over the past 30 years, and I have written over 75 books covering SQL on every database platform. I have never seen SQL so robust as I have with Snowflake. Almost every…

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A fortune 100 company had changed its on-premises strategy to the cloud and needed to move its on-premises systems to the AWS cloud.  It wanted to migrate its Netezza, Oracle, and Teradata systems to Amazon Redshift, Snowflake, MySQL, and Postgres. At the time, they decided that their best choice was to use Amazon’s Data Migration Services (DMS).  After finding that DMS was not reliable enough for this massive project, they began a Proof of Concept with the Nexus Pro desktop and Nexus Server combination.

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NExus core server makes data movement easier for DBAs, IT, and business users.

The two concepts in our Big Data vision is the user’s desktop and the database server.  The Nexus desktop allows a user to access any data, at any time, anywhere from their desktop or laptop, no matter whether they are at the office, a coffee shop, or home.  The Nexus Server sits in between the many different database platforms, both on-premises and on every cloud, and manages and controls the data movement between systems.  Users use the desktop to build anything and everything, but they have the option to run it from their desktop or the Server.

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An international semiconductor company was running a complex query on Teradata and wanted automatically to create a table on their MySQL system.  We came up with two solutions:

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A large bank was consolidating on Teradata and needed Oracle, SQL Server, and DB2 users to move critical data to their Teradata sandbox.  We invented the Nexus multi-database tree, where you can see two systems trees side by side.  Users can click-and-drag to move a single-table or an entire database,  which creates the table(s) on the Teradata system.

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A sizeable primary healthcare provider requested the Nexus Pro and Nexus Server to migrate data from their Teradata and SAP HANA systems directly to Google BigQuery.  This herculean effort might take some software companies years to develop, but we expect to finish with 30-days. 

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In good times and in bad, it is essential to save money.  So many companies are using dozens of different tools to access data, and the penalty is millions of dollars per year.  And the truth of the matter is most of these tools don’t share reports or queries with others.  It is every man and woman for themselves. It may sound too good to be true, but you can give everyone a much better toolset, and allow everyone to be on the same team.  You also need your people to access data both on-premises or in the cloud.  And unfortunately, in today’s climate, you need a tool where everyone can perform all of their duties from home, but execute the work from an internal Server.

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They say you can’t be in two places at one time, but I beg to differ.  You can work from home, but access data across any platform as if you were sitting in your corporate office.  The future of computing is accessing any data, at any time, anywhere, and doing so from your home. You do this with laptop software coordinating with a Server. 

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Federated queries are a combination of hardware and software working together like dance partners that make it an art.  A federated query joins tables together from different systems.  Federated queries are the definition of accessing any data, at any time, anywhere. 

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I can teach you Snowflake analytics!  Today we are going to learn about Cume_Dist. Cume_Dist returns the cumulative distribution of a value within a set of values. It represents the number of rows with values less than or equal to that row’s value divided by the total number of rows. The returned value of the CUME_DIST function is greater than zero and less than or equal one.

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I can teach you Snowflake analytics!  I will bet you have never seen a listagg analytic! Some major companies use the listagg analytic for their email marketing campaigns.  They cleverly find out the last three web pages the customer went to on their website, and then they send them a customized email offering sales on the products they were viewing last. Let me show you exactly how it works.

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I can teach you Snowflake analytics!  I have never seen a database do analytics better than Snowflake.  Last week we taught you Lead, and this week we are teaching you Lag. You use a Lead to place the value from the next row on the current line of the answer set.  You can then see today’s value, and on the same line, see tomorrow’s value.  You do the opposite for the Lag.  You can see today’s value, and on the same line, see yesterday’s value. 

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I can teach you Snowflake analytics! I have never seen a database do analytics better than Snowflake. This week we are working on the Lead. You use a Lead to place the value from the next row on the current line of the answer set. You can then see today’s value, and on the same line, see tomorrow’s value.

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I can teach you analytics!  I have never seen a database do analytics better than Snowflake.  This week we are working on the Moving Difference, which is interchangeable with MDIFF. You use a Moving Difference (MAVG) to compare the difference between the value from two different rows.  For example, you can see your Daily_Sales from this Monday, and then see the difference between the Daily_Sales from last Monday. 

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