Google Cloud Next ‘20: OnAir and in the Cloud with Maven Wave – Data Analytics Week

Across screens worldwide, Google Next ‘20: OnAir attendees are taking a deeper dive into today’s most commanding cloud topics. Led by Google Cloud experts and featured guests, the all-digital event is helping leaders solve some of their most crucial challenges with fresh on-demand content, interactive experiences, and more. The nine-week event is halfway through, but the content is available on-demand by building a customizable playlist.

Whether you are looking to gain valuable insight into the industry’s hottest topics, enhance your skills via Google Cloud’s Learning Hub and Cloud Study Jams, or network, Google Next ‘20: OnAir has you covered. 

Here at Maven Wave, we’ve been tackling the week’s theme each Monday with a related Q&A session via our ongoing “OnAir and in the Cloud” blog series. In case you missed our security week blog, click here. For our infrastructure week blog, click here, and for our inaugural blog that took a deep dive into productivity & collaboration week, click here.

As we move into this week’s Next theme, Data Analytics, you can expect to learn more about the latest innovations in Google Cloud’s smart analytics platform that will help businesses analyze data seamlessly in a multi-cloud world. Moreover, attendees will get to explore how to leverage Google Cloud to accelerate their data-driven digital transformations.

Whether you are just beginning to lead your company on a data-powered journey or are looking to scale data-driven insights across your organization, there’s no denying that data is vital in today’s digital era. For everything data analytics related, keep reading for our Q&A with three expert Mavens: 

  • Charlie Sanders, Senior Principal – Data Delivery Lead
  • Chris Vankula, Principal – Marketing Analytics
  • Alex Mendoza, Principal Consultant 

Q: In today’s data-driven marketing world, how can Google Cloud’s smart analytics platform help analyze data? 

Google Cloud’s smart analytics platform can help analyze data to benefit customers in a number of ways:

  • With real-time data flowing in and fast analytics, GCP can spot trends and surface insights that empower the analytics teams and their stakeholders to leverage those trends in a way that is a true competitive advantage.
  • Customers expect more than ever these days. GCP can help deliver fast, accurate customer responses resulting in higher customer satisfaction.
  • The smart analytics platform can help predict customer actions that significantly affect revenue, such as new product sales, product returns, potential customer LTV (lifetime value) for media decisions, and customer satisfaction and potential churn.
  • The smart analytics platform can help provide a higher level of customer personalization with product upsell/cross-selling, ad or email next-best-action recommendations, and sales enablement tools.

Q: As business environments evolve, how can leaders better understand their data in an actionable way? 

Business leaders should formulate a culture that thrives and takes action on data. We have found that actionable data has these qualities:  

  • Timely: The data is modern and timely. It allows teams to receive and interpret information, and ultimately make actionable business decisions.
  • Trustworthy: The business must know that the data it’s receiving is of high quality and can tie-out to key systems of record.   
  • Valuable: KPI or intelligence being broadcasted can influence key business objectives, cost savings, or revenue potentials.
  • Accessible: Creating a data-driven culture and fostering invention is a result of investing in quality data. Allowing team members to access and experiment with data drives innovation. 

We like to remind our clients that getting data “in” is part of the job. The subsequent part of the job is to influence the business stakeholder to trust the data and the processes that facilitate the generation and movement of it. It’s critical for stakeholders to use relevant data for crucial decision making, not just transactional reporting. We encourage our clients not to view data as simply data, but rather to view it as a “data product.” Products that are popular with the business and build loyalty follow the Timely, Trustworthy, Valuable, and Accessible approach.

Q: How can businesses run analytics in a multi-cloud environment?

What a great question! We often use the following antidote with our clients…..”You can dip a hammer into a paint bucket and try to paint a wall, that doesn’t mean that it will do a great job.” 

Here are a few creative ways of approaching this puzzle:

  • Selecting the right analytical tool: There are plenty of BI / Analytical tools in the marketplace that can help achieve analytics integration as they can connect to multiple clouds. No need to move the data in or out of a cloud, simply point your analytical tool to the appropriate cloud.
  • Select the right cloud: While we love GCP & BigQuery, we are all about selecting the right tool for the right job. As this is becoming more of a trend, Maven Wave recently executed a partnership with Striim. Striim allows our clients to choose the cloud that works best for their unique analytical needs and easily moves data.  
  • Love BigQuery? Take it to the other clouds! We are so excited that BigQuery will now be able to query across other clouds. BigQuery Omni is going to be an analytics game changer.    

Q: What are some of the challenges enterprises face when migrating legacy data warehouses and data lakes to the cloud?

  • Forget about “Big Data.” Focus on the “right” data.
  • Don’t get lost in analysis paralysis of the “how” or “what” or “who.”
  • Don’t replicate like for like with the “hope” that down the road, another project will get spun up to “clean” up.
  • Perform an organization, platform, and skill assessment. 
  • Go for incremental wins.
  • While lift and shift may be easy, it may not be the best long-term option.
  • A little incentive goes a long way.
  • Shift away from the “why” to the “why not” or “why haven’t we.”  
  • Don’t worry about the ants when the elephants are running by.  
  • Your business processes or IT operation process will also need to be revamped. They can’t be an afterthought. 

Old on-prem limitations don’t apply in the cloud. Get creative. Focus on the possibilities.

Q: AI and machine learning technologies make it possible to amp up the detection of insights in large volumes of data. Where do you see these capabilities heading in the future?

More data; more problems. AI and Machine learning are now being deployed to detect data quality early in the ingestion process to enable faster analytics downstream. No need to waste “empty calories” on processing data, storing data, and managing data that won’t provide any value. We recently deployed this approach to one of our clients. It saved them time, energy, and money! The applications for AI and ML are only limited by creativity. 

Q: Maven Wave holds Google Cloud Partner Specializations in Marketing Analytics and Data Analytics. How does this benefit customers?

This specialization benefits the customer because Maven Wave has already been heavily vetted by Google. In order to obtain a Google Cloud Partner Specialization, a partner must go through a rigorous process of demonstrating (by presenting our work product) to Google that they have not only served customers in a specific specialization but also that the engagement was done at a very high strategic level. So a customer can be sure that Maven Wave has proven expertise across several clients and that Maven Wave has strategic methodologies already in place to benefit the client and accelerate time to value.

Maven Wave’s Suggested Sessions for Google Next OnAir Data Analytics Week:

Be sure to check back next week for the next edition of Google Cloud Next ‘20: OnAir and in the Cloud with Maven Wave. Next week, we’ll take a closer look at how Google Cloud enables enterprises to migrate, manage, and optimize traditional databases. Plus, we’ll explore building new applications with modern ones.

August 10th, 2020
DATA ANALYTICS & MACHINE LEARNING

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2020-08-10T12:49:17-05:00