TechValidate Research on Google Cloud Data Analytics

These pages present data that TechValidate has sourced via direct research with verified customers and users of Google Cloud Data Analytics. TechValidate stands behind the authenticity of all published data. Learn more »



163 Customers Surveyed

1,521 Data Points Collected

11 Published TechFacts

23 Published Charts

42 Published Case Studies



Selected Research Highlights


Looker Customer Research

How have you seen a return on your investment in Looker?

Reduced development, maintenance costs
76%
Improved customer satisfaction
62%
Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
38%
Reduced customer churn
19%

Google BigQuery Customer Research

By what percentage did your organization improve in the following with BigQuery?

100%+ 75-100% 50-75% 25-50% Up to 25%

Advanced analytics & ML
Streaming & Real-time insights
Increased agility & faster insights
Security
Query data living in external data sources like sheets, Marketo, etc. for richer insights

Google Cloud Customer Fact

Donde Search reduced IT maintenance by up to 20% since using Google Cloud.

Looker Customer Statistic

79% of organizations agreed with the following statement:

“Leveraging embedded analytics with Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class data products that keep our development teams focused on core competencies.”

Google BigQuery Case Study

SulAmérica

Introduction

SulAmérica migrated up to 50TB from their traditional data warehouse to BigQuery. By migrating off their Cloudera/Hadoop system to BigQuery, SulAmérica was able to improved scale, security, reliability, and integrations with external data sources and tools.

“Powerful and easy to start and grow without infrastructure limits. Pay-as-you-go model with serverless solutions are worthwhile.”

Challenges

SulAmérica Faced the following pain points prior to their BigQuery migration:

  • Performance outages
  • Long compute and storage capacity planning
  • Growing database operations management
  • An upcoming hardware refresh
  • An upcoming software license renewal
  • Pressure from management / board
  • Pressure from line of business for faster insights
  • Migrated off the following legacy systems to BigQuery:
    • Cloudera/Hadoop
  • Evaluated the following data warehouse provider before adopting BigQuery:
    • AWS Redshift
  • Use Case

    The key features and functionalities of Google BigQuery that the surveyed company uses:

    • Used Informatica for implementing their BigQuery migration.
    • Migrated up to 50TB from their traditional data warehouse to BigQuery in total.
    • Their BigQuery migration took 12+ months.

    Results

    SulAmérica achieved the following results with Google BigQuery:

    • Business value achieved after migrating to BigQuery:
      • Improved scale
      • Improved security & reliability
      • Integrated with external data sources & tools
    • Improved in the following areas after using BigQuery:
      • Improved advanced analytics & ML: up to 25%
      • Increased agility & faster insights: 75-100%
      • Improved security: 75-100%
      • Improved query data living in external data sources (sheets, Marketo) for richer insights: 75-100%
    • Received insights 20x faster after investing in BigQuery.
    • Took on 5-10 net new data & analytics projects as a result of moving to BigQuery in a year.

    Looker Case Study

    Prisa Noticias

    Introduction

    This case study of Prisa Noticias is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

    “Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

    Challenges

    The business challenges that led the profiled company to evaluate and ultimately select Looker:

    • Used the following bi platforms before Looker:
      • Google Data Studio
      • Microsoft PowerBI
    • Pain points that led them to begin looking for a new analytics platform:
      • Providing access to insights/self-service
      • Barriers to entry – previous solution was difficult for people to extract the value they needed
      • Real time analysis
    • Faced the following business challenges prior to implementing Looker:
      • Accessing a real-time view of the business
      • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
    • Experienced the following challenges with data before using Looker:
      • End-user frustrations – self-service, ease of use, and action

    Use Case

    The key features and functionalities of Looker that the surveyed company uses:

    • Priorities as a data leader:
      • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
      • Improving operational visibility and inform strategic decision-making
      • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
      • Proving return on high-cost investment in data

    Results

    The surveyed company achieved the following results with Looker:

    • Experienced the following benefits since implementing Looker:
      • Empowered users to self-serve
      • Freed up their data team to focus on more strategic initiatives
      • Broke down data silos -encourage cross-functional data-driven collaboration
      • Provided the users an actionable interface that allows more than just reporting
      • Offered better visualizations and dashboards
      • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
      • Delivered data to external users such as customers or partners
    • Saw a return on their investment in Looker within 1-6 months.
    • Increased their revenue after implementing Looker in the following ways:
      • New Customer acquisition
      • Decreased customer churn
    • Looker allowed them to:
      • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
      • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
      • Make the company more data-driven by giving their team secure access to the data they need
      • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
      • Productize and eventually monetize data by serving it back to customers and partners


    More to Explore