The Data Warrior

Changing the world, one data model at a time. How can I help you?

Archive for the tag “#bigdata”

Snowflake and Spark, Part 1: Why Spark? 

Snowflake Computing is making great strides in the evolution of our Elastic DWaaS in the cloud. Here is a recent update from engineering and product management on our integration with Spark:

Spark

This is the first post in an ongoing series describing Snowflake’s integration with Spark. In this post, we introduce the Snowflake Connector for Spark (package available from Maven Central or Spark Packages, source code in Github) and make the case for using it to bring Spark and Snowflake together to power your data-driven solutions.

Read the rest of the post: Snowflake and Spark, Part 1: Why Spark?

Enjoy!

Kent

The Data W

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Cloud Data Warehousing for Dummies

As we all know, cloud is the big thing these days. Getting bigger everyday it seems.

It may get even bigger than Big Data!

If you, like me, are a data warehousing or BI professional, you have probably been wondering how this all fits in the cloud world. You may have even heard of data warehousing  “in the cloud”.

But what does that really mean? What is a cloud data warehouse?

Well thanks to Snowflake Computing, it just got a little easier to answer this question.

They sponsored the development of a new book called Cloud Data Warehousing for Dummies. Yup, an actual Dummies guide for this. And yes, yours truely, got to have a hand in editing and writing the book.

And the best part – it is FREE!

clouddw_dummies

Researching and helping to write the book was very educational for me. I learned a lot in the process about what constitutes a cloud data warehouse, the difference between a platform in the cloud and a real service in the cloud, and what characteristics folks should look for when choosing one.

I also learned to say “on-premises” instead of “on-premise.” 🙂

Content

The chapters of the book cover:

  • An introduction to cloud data warehousing
  • Why the modern data warehouse emerged
  • The criteria for selecting a modern data warehouse
  • On-premises vs cloud data warehousing
  • Comparing cloud data warehousing solutions
  • A six-step guide to choosing a cloud data warehouse

It also includes several real-world customer case studies.

Even though Snowflake sponsored the book, it is vendor agnostic. It really is a book designed to get you introduced to the concepts and to get you thinking about what you might want in a cloud-based data warehousing system.

It is ideal for anyone who is considering making that transition to the cloud.

So head on over to this site and download your FREE copy today!

To infinity and beyond!

Kent

The Data Warrior (with his head in the clouds)

P.S. Forward this to a friend so they can download a copy too!

 

 

Drill to Detail Podcast: Data Modeling, Data Vault, and Snowflake!

My good friend Mark Rittman has embarked on a new adventure as an independent analyst and consultant. As part of his new venture Mark started a new podcast series on iTunes that he calls Drill to Detail where he will feature interviews discussing a range of topics related to data warehousing, business intelligence, analytics, and big data.

I was honored to be asked to take part in this new venture and got to spend a hour with Mark a few weeks back recording what is now Episode 5 of the series. In this interview we talk about:

The podcast is about 60 minutes with each topic being about 20 minutes (so feel free to skip ahead if you are short on time). Please have a listen and let us know what you think in the comments below.

Cheers!

Kent

The Data Warrior

P.S. I will be speaking on these and related topics at a bunch of events over the next few weeks. Check out my speaking schedule and join me in person if you can!

Top 3 Tips for Staying Current in the Evolving World of Data Warehousing

The world of data warehousing and analytics has changed! With the advent of Big Data, Streaming Data, IoT, and The Cloud, what is a modern data warehousing professional to do? It may seem to be a very different world with different concepts, terms, and techniques. Or is it?

This is a question I ask myself all the time. So how do you keep up?

Here is what I do:

1 – Follow the Leaders

Yes, social media! Mostly, I use Twitter. I follow the industry thought leaders and analysts like Claudia Imhoff, Tamara Dull, Howard Dresner, Philip Russom, Cindi Howson, and many others. Not only do I see what they are thinking (and speaking) about, but I get to see what they are reading.

2 – Meet the Leaders

While reading books and online articles is great, there is nothing that replaces face to face communication. And the best way to do that is attend educational events where they are speaking. These days that could mean everything from local meet-ups, to regional conferences (like RMOUG), vendor roadshows, and larger annual events (like the recent Oracle OpenWorld).

For meet-ups, simply go to https://www.meetup.com/ and sign up (for free). You can search for meet-ups in your local area by topic. You may be surprised how many there are nearby and how often they have event. This is a great way to network with other professional in your local community.

To learn from the industry leaders, look to larger national and international events. In the data warehousing and analytics world that means groups like The Data Warehouse Institute (TDWI). They have local chapters and run larger national events on a regular basis (the next one is in October in San Diego). Another group I am associated with is DAMA International which also sponsors local chapters, national and international events.

And of course your vendors and solution providers may run their own events, like the Snowflake Cloud Analytics city tour.

3- Be a Leader

Volunteer! Yes by getting involved with these meet-ups, associations, and user groups, whether locally or nationally, you not only get to give back to the community, but you will often benefit by getting to know and speak with leaders one on one in a less formal environment.

Start off small by helping organize a meeting, or getting the refreshments. Help with the web site or the mail list. If the group you choose runs a conference, help with the paper selection process (you will learn a ton reading the abstracts). And then, when you are ready, become a speaker yourself. There is no better way to learn than to try to teach what you know to someone else.

I have been helping with user group conferences and events for nearly 30 years now and have never regretted a minute of the time spent.

 

So those are my top 3 tips for how you can stay fresh and informed and ahead of the game in this crazy world of data warehousing, big data, and the cloud.

Seems to be working for me.

Keep Learning!

Kent

The Data Warrior

P.S. One of our Snowflake customers, IAC Publishing Labs (owners of Ask.com), won the TDWI Best Practice award for the Emerging Technologies and Methods category and Keith Lavery will be speaking about the project at the TDWI Executive Summit in San Diego on Monday, October 3rd.

P.P.S.  And don’t forget to follow some of the leaders at Snowflake like @bob_muglia and @jonb_snowflake.

 

One more time: Do we still need Data Modeling?

More specifically do we still need to worry about data modeling in the NoSQL, Hadoop, Big Data, Data Lake, world?

This keeps coming up. Today it was via email after a presentation I gave last week. This time the query was about the place of data modeling tools in this new world order.

Bottom line: YES, YES, YES! We still need to do data modeling and therefore need good data modeling tools and skills.

Snowflake with RI

A picture can say so much!

 

In order to get any business value out of the data, regardless of where or how it is stored, you have to understand the data, right?

That means you have to understand the model of the data. Even if the model (or schema) is not needed upfront to store the data (schema-on-write), you must discern the model in order to use it (schema-on-read).

It is (mostly) impossible to get repeatable, auditable metrics, KPIs, dashboard, or reports that bring value to the business without understanding the semantics of the data – which means you at least need a conceptual or logical model.

And if you want/need to join data from multiple source then you really have to understand each source or there is no way to properly join it all together to get meaningful results.

There are a few data cleansing, discovery,and “virtualization” tools out there that will help you figure out those relationships but they are expensive and mostly rely on standard data profiling techniques to find similar data objects across the sets and propose “relationships”. Some allow for the definition of fairly sophisticated matching rules including customizations. But a human still needs to figures those out, test, and validate the results.

In the end you still have to know your data.

One of the best ways to do that, in my opinion, is to model that data. Otherwise your data lake will likely become a data swamp!

So keep your data modeling tool and keep building your data dictionary with your business folks.

Final Stage Table

A good modeling tool can act as a visual data dictionary too!

If you agree with me, please share on social media!

#LoveYourData

Kent

The Data Warrior

P.S. If you need a good modeling tool, check out Oracle SQL Developer Data Modeler. And check out my books and training offering for SDDM on the blog sidebar.

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