Last week Google Cloud not only rocked the analytics world with news of acquiring Kaggle, they made over 100 announcements and hosted more than 10,000+ attendees at the annual Next event. Although Google Cloud had less than half of Amazon re:Invent 2016 attendance, the big enterprise wins, impressive cloud data warehousing and artificial intelligence innovations combined with GSuite productivity app additions and key industry partnerships clearly reveal significant market momentum. You can watch the keynotes and Google Next sessions on YouTube.

Highlighted Enterprise Big Wins

As first reported in my Winter 2017 Industry Pulse magazine, whoever is selling Google Cloud in my area of the world is winning big deals. I had heard quiet whispers about Home Depot and other enterprise accounts selecting Google BigQuery. Now I know my sources were right. I was awestruck to see Home Depot on stage. I personally know that Home Depot digs in deep and tests thoroughly before selecting new solutions.

Niantic, the group that created Pokémon GO, eBay and several other massive customers also shared success stories adopting Google Cloud. Pokémon GO’s popularity rapidly surged to 50X the initial target, ten times the worst-case estimate. The joint Niantic + Google CRE (Customer Reliability Engineering) teams pulled off an incredible technical feat in the epic worldwide launch. Their story is a good read.

From what I can tell, all of the major cloud vendors now help you move to cloud. I have seen quite a few peers hired into cloud solution architect roles. Concurrently partner ecosystem, system integration consulting firms seem to be feeling the pain of losing talent and competing with cloud vendors for that same work. Sadly I suspect the cloud vendor mass hiring of talent to get customers to cloud will end up with layoffs after most of the lift and shift is done. I’ll save that topic for another day. Let’s get back to Google.

Impressive Innovations

Over the past few weeks we have seen Google making waves with news of a super cool, globally distributed cloud relational database service called Cloud Spanner. Here are my favorite Google Next analytics and data science highlights.

Cloud Data Prep

Congratulations to Trifacta! Just this past January, Trifacta had a fantastic release that I covered on the blog. Thus as I watched Google announce a Cloud Data Prep private beta, I immediately recognized Trifacta as the power behind it. To learn more or sign up for that beta, visit Google Cloud’s web site.

Python for Google Cloud Dataflow

Google Cloud Dataflow is a “serverless” approach to removing complexity and operational overhead from data processingin batch as well as stream-processing scenarios. Today, Google announced general availability of the Python SDK for Cloud Dataflow. The SDK comes directly from Apache Beam, and its implementation on Cloud Dataflow has proven popular for a variety of use cases where Python is commonly used, from ETL, to orchestrating large-scale image processing, to data preparation for machine learning.

Google Data Studio

Free Google Data Studio is now available in over 180 countries.

Google Data Studio

Google now offers free Google Data Studio in over 180 countries. Google Data Studio is quite nice for Google Analytics related reporting. It also works with non-Google Analytics data sources. Although it is in beta, the user experience is coming along nicely. The templates are beautiful and the report design is fairly easy to learn. I’ll showcase that solution in an upcoming article.

Google Cloud Datalab

Another really cool app is Google Cloud Datalab. Google Cloud Datalab is now in GA. This interactive data science workflow tool makes it easy to do iterative model, data analysis and data visualization in a Jupyter notebook-based environment using standard SQL, Python and shell commands.

Google Data Lab

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models using awesome TensorFlow or Cloud Machine Learning Engine on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily. Cloud Datalab is built on popular Jupyter (formerly IPython), which boasts a thriving ecosystem of modules and a robust knowledge base. Cloud Datalab enables analysis of your data on Google BigQuery, Cloud Machine Learning Engine, Google Compute Engine, and Google Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions).

Great Cloud Machine Learning Services

Google is a market leader when it comes to machine learning in the cloud. This week we saw that leadership extend to analyzing video in fascinating demos. Touted as a first of its kind, Google showed Cloud Video Intelligence API (private beta) searching and identifying video content. On the product launch page, you can also test video to see this analysis for yourself. It is compelling and has a wide variety of use cases from security to content management.

Google Cloud Video API

Cloud Vision API (GA) is now GA and offers new capabilities for enterprises and partners to classify a more diverse set of images. The API can now recognize millions of entities from Google’s Knowledge Graph and offers enhanced OCR capabilities that can extract text from scans of text-heavy documents such as legal contracts or research papers or books.

Cloud Machine Learning Engine (GA)  is now generally available. This solution is for organizations that want to train and deploy their own models in the Google Cloud.

Machine Learning Advanced Solution Lab (ASL) allows organizations to partner directly with Google staff to apply Machine Learning to solve high-impact challenges. The ASL is a unique opportunity for technical teams to work side-by-side with Google’s machine learning experts in Google dedicated facilities.

In the ongoing battle for finding top machine learning talent, Google announced a Machine Learning Startup Competition in collaboration with venture capital firms Data Collective and Emergence Capital, and with additional support from a16z, Greylock Partners, GV, Kleiner Perkins Caufield & Byers and Sequoia Capital. I expect we will see many more “machine learning competitions” from vendors each year as we enter the era of digital transformation.

More Cloud Database Services

BigQuery Data Transfer Service also is in private beta. This new service makes it easy for users to move Google-managed advertising datasets. With just a few clicks, marketing analysts can schedule data imports from Google Adwords, DoubleClick Campaign Manager, DoubleClick for Publishers and YouTube Content and Channel Owner reports.

New cloud databases and database features round out the cloud data platform including Cloud SQL for Postgre SQL (beta), Microsoft SQL Server Enterprise (GA) is available on Google Compute Engine, plus support for Windows Server Failover Clustering (WSFC) and SQL Server AlwaysOn Availability (GA), Cloud SQL for MySQL improvements and federated query on Cloud Bigtable for massive analytic or operational workloads that require low latency and high throughput particularly common in Financial Services and IoT use cases.

More Price Cuts

This past week Google announced compute engine price cuts of up to 8%. Committed Use Discounts of up to 57% off of list price, in exchange for a one or three year purchase commitment paid monthly, with no upfront costs and the free trial extended to 12 months. This makes it more comparable to Amazon’s free one year offer. Numerous other free developer applications are available. See Google Cloud Platform Free Tier page for details.

Committed Use Discounts of up to 57% off of list price.

As we continue to see in the intense rivalry between providers, price cuts today are the norm. Once we all get to the cloud… I suspect we will see the reverse. Public companies do need to continually show growth and profits. Loss leader price cuts are not sustainable in the long-term.

Women in Big Data Analytics

I also sincerely appreciated seeing women in leadership on the Google Next stage. Diane Greene, Senior Vice President, Fei-Fei Li, Chief Scientist, Cloud AI & ML, Alison Wagonfeld, Vice President of Marketing and numerous women product managers demonstrated solutions in keynotes. Gartner’s annual event last week was also wonderfully women in tech friendly. It was refreshing and encouraging to see…especially since I have been discouraged the past few years. I have not seen diversity shown at Amazon or Microsoft events. Seeing Google and Gartner being diverse at the top, not just at the bottom, gave me hope for the next generation.

For More Information

I have barely touched on all of the news from the Google Next event. One key takeaway for me is that Google Cloud is a phenomenal force to be reckoned with. The whispers I heard last year sounded more like shout outs last week. Thus I need to learn Google Cloud too.

Google Cloud is a phenomenal force to be reckoned with.

What about GSuite? Gee, I don’t know. I have not yet made the switch from comfortable Office 365. I do know that almost all of my company’s Silicon Valley customers use Apple Macs and GSuite (Google Docs). I even noticed that several larger firms in my network do not use Microsoft Office. Could there finally be viable competition in productivity apps again?

Competition is a good thing for customers.

I am totally addicted to my heavy Lenovo laptop with downgraded Windows 8.1. I refuse to upgrade to Windows 10 again after experiencing frequent blue screens. I also don’t care for all the extra Windows 10 “monitoring”.

After the latest Wikileaks, it is fair to say spyware is literally everywhere. Sigh… On the bright side, I am a boring data enthusiast that drinks too much Diet Mountain Dew, loves her husband, fur-kid, sunshine, flowers, ocean, tropical fish and the great outdoors. My hair is usually tied into a messy bun while I endlessly type on my laptop keyboard. No need to spy on me. Nothing to see here.

For more information on Google Cloud offerings, check out the following resources.