aster.cloud aster.cloud
  • /
  • Platforms
    • Public Cloud
    • On-Premise
    • Hybrid Cloud
    • Data
  • Architecture
    • Design
    • Solutions
    • Enterprise
  • Engineering
    • Automation
    • Software Engineering
    • Project Management
    • DevOps
  • Programming
    • Learning
  • Tools
  • About
  • /
  • Platforms
    • Public Cloud
    • On-Premise
    • Hybrid Cloud
    • Data
  • Architecture
    • Design
    • Solutions
    • Enterprise
  • Engineering
    • Automation
    • Software Engineering
    • Project Management
    • DevOps
  • Programming
    • Learning
  • Tools
  • About
aster.cloud aster.cloud
  • /
  • Platforms
    • Public Cloud
    • On-Premise
    • Hybrid Cloud
    • Data
  • Architecture
    • Design
    • Solutions
    • Enterprise
  • Engineering
    • Automation
    • Software Engineering
    • Project Management
    • DevOps
  • Programming
    • Learning
  • Tools
  • About
  • Data
  • Public Cloud

Faster Time To Value With Data Analytics Design Patterns

  • aster.cloud
  • November 17, 2021
  • 4 minute read

Companies today are inundated with vast amounts of data from various sources. This overwhelming amount of data is meant to benefit the company, but often leaves data teams feeling overwhelmed, which can create data bottlenecks and result in a slow time to value. In fact, only twenty seven percent of companies agree that data and analytics projects produce insights and recommendations that are highly actionable (Accenture). This means that nearly 3 in 4 companies are not unlocking value in their data, which poses a huge challenge for organizations trying to move the needle and drive real business results. We at Google Cloud, however, saw opportunity in this challenge, which is why we created Data Analytics Design Patterns: cross-product technical solutions designed to accelerate a customer’s path to value realization with their data. These industry solutions bring together product capabilities alongside design methodology, open source deployable code, data models, and reference architectures to accelerate your business outcomes.

1 Data Analytics Design Patterns.jpg

With Data Analytics Design Patterns, you get access to more than 30 ready-to-deploy data analytics solutions. Design patterns leverage the best of Google and our rich partner ecosystem, including Technology Partners & System Integrators. In this blog, we will cover 3 examples on how a design pattern can be applied to unlock the value of data:


Partner with aster.cloud
for your next big idea.
Let us know here.



From our partners:

CITI.IO :: Business. Institutions. Society. Global Political Economy.
CYBERPOGO.COM :: For the Arts, Sciences, and Technology.
DADAHACKS.COM :: Parenting For The Rest Of Us.
ZEDISTA.COM :: Entertainment. Sports. Culture. Escape.
TAKUMAKU.COM :: For The Hearth And Home.
ASTER.CLOUD :: From The Cloud And Beyond.
LIWAIWAI.COM :: Intelligence, Inside and Outside.
GLOBALCLOUDPLATFORMS.COM :: For The World's Computing Needs.
FIREGULAMAN.COM :: For The Fire In The Belly Of The Coder.
ASTERCASTER.COM :: Supra Astra. Beyond The Stars.
BARTDAY.COM :: Prosperity For Everyone.

  1. Improve mobile app experience with Unified App Analytics
  2. Maximize digital shop’s revenue with Price Optimization
  3. Protect internal systems from security and malware threat with Anomaly Detection

Unified App Analytics

If mobile apps are part of your go-to-market strategy, you have several data sources that can provide invaluable customer insights. In addition to tools such as CRM (e.g. Salesforce) and customer care (e.g. Zendesk), you likely use Google Analytics to log app events and Firebase Crashlytics to gather data about app errors. But can you easily combine back-end server data with app front-end data to unlock customer insights?

Read More  How To Install And Configure Couchbase DB In Ubuntu

The Unified App Analytics design pattern makes it easy to plug all the disparate data sources into a single warehouse (BigQuery) and start analyzing it with a Business Intelligence tool (Looker). Once you have a complete and real time view of your customer experience with your app, you can take action. For example, if you notice an increase in app errors, you can quickly combine your Crashlytics data with your CRM data to narrow down the crashes with the highest revenue impact and prioritize their resolution. Further, you can automate your issue resolution workflow by creating a rule for any future crash that impacts a subset of VIP customers.

2 Data Analytics Design Patterns.jpg
Unified App Analytics turns your data warehouse into an actionable customer insights tool

With the Unified App Analytics design pattern, you’ll gain access to valuable insights about your user experience with your app so you can inform your future app strategy. For example, NPR, an American media company, increased user engagement by showing content that better mapped to listener interests and behaviors.

Price Optimization

In a competitive and hectic global marketplace, strategic pricing matters more than ever, but often projects are consumed by the tedium of standardizing, cleaning, and preparing data—from transactions, inventory, demand, among other sources.

Price Optimization solution allows retailers to build a data driven pricing model. The solution consists of three main components:

  • Dataprep by Trifacta: integrates different data sources into a single Common Data Model (CDM). Dataprep is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis, reporting, and machine learning.
  • BigQuery: allows you to create and store pricing models in a consistent and scalable way as a serverless Cloud Data Warehouse service
  • Looker dashboards: surface insights and enable business teams to take action with enterprise ready BI platform
Read More  Google Launches Last Mile Fleet Solution And Cloud Fleet Routing API to Help Fleet Operators Optimize Delivery Operations, Meet Pandemic-Driven Challenges

With the Price Optimization design pattern from Google Cloud and our partner Trifacta, you’ll be able to rapidly unify multiple data sources and create a real-time and ML-powered analysis, leveraging predictive models to estimate future sales. For example, PDPAOLA, an online jewelry company, doubled sales with dynamic pricing adjustments enabled by a single data view.

3 Data Analytics Design Patterns.jpg

Anomaly Detection

Organizations need to anticipate and act on risks and opportunities to stay competitive in a digitally transforming society. Anomaly detection helps organizations identify and respond to data points and data trends in high velocity, high volume data sets that deviate from historical standards and expected behaviors, allowing them to take action on changing user needs, mitigate malicious actors and behaviors, and prevent unnecessary costs and monetary losses.

The Anomaly Detection design pattern uses Google Pub/Sub, BigQuery, Dataflow, and Looker to:

  • Stream events in real time
  • Process the events, extract useful data points, train the detection algorithm of choice
  • Apply the detection algorithm in near-real time to the events to detect anomalies
  • Update dashboards and/or send alerts

The challenge of finding the important insights and anomalies in vast amounts of data applies to organizations across all industries and lines of business, but is especially important to protecting the security of an organization. For example, TELUS, a national communications company, modernized their security analytics platform leveraging this pattern, allowing them to detect anomalies in near real time to detect and mitigate suspicious activity.

Get started

Turn your data into business outcomes with Google Cloud and our broad partner ecosystem by deploying Data Analytics Design Patterns at your organization. There are more than 30 Data Analytics Design Patterns ready for you to use. We have more than 200+ more ideas in the pipeline, so be sure to check in regularly as new patterns will be added soon.

Read More  Silos Are For food, Not Data—Tackling Food Waste With Technology

To dive deeper and find out more about how Data Analytics Design Patterns can help your organization accelerate use cases and create faster time to value, TELUS

 

By Kathryn Petrini Product Marketing Manager, Google Cloud | Justyna Bak Product Strategy and Marketing Lead, Google Cloud
Source Google Cloud Blog


For enquiries, product placements, sponsorships, and collaborations, connect with us at [email protected]. We'd love to hear from you!

Our humans need coffee too! Your support is highly appreciated, thank you!

aster.cloud

Related Topics
  • Data Analytics
  • Google Cloud
  • Unified App Analytics
You May Also Like
Getting things done makes her feel amazing
View Post
  • Computing
  • Data
  • Featured
  • Learning
  • Tech
  • Technology

Nurturing Minds in the Digital Revolution

  • April 25, 2025
View Post
  • Computing
  • Public Cloud
  • Technology

United States Army Enterprise Cloud Management Agency Expands its Oracle Defense Cloud Services

  • April 15, 2025
DeepSeek R1 is now available on Azure AI Foundry and GitHub
View Post
  • Public Cloud
  • Technology

DeepSeek R1 is now available on Azure AI Foundry and GitHub

  • February 2, 2025
View Post
  • Data
  • Engineering

Hiding in Plain Site: Attackers Sneaking Malware into Images on Websites

  • January 16, 2025
Cloud platforms among the clouds
View Post
  • Computing
  • Learning
  • Public Cloud

Best Cloud Platforms Offering Free Trials for Cloud Mastery

  • December 23, 2024
Vehicle Manufacturing
View Post
  • Hybrid Cloud
  • Public Cloud

Toyota shifts into overdrive: Developing an AI platform for enhanced manufacturing efficiency

  • December 10, 2024
IBM and AWS
View Post
  • Public Cloud

IBM and AWS Accelerate Partnership to Scale Responsible Generative AI

  • December 2, 2024
COP29 AI and Climate Change
View Post
  • Public Cloud
  • Technology

How Cloud And AI Are Bringing Scale To Corporate Climate Mitigation And Adaptation

  • November 18, 2024

Stay Connected!
LATEST
  • 1
    Just make it scale: An Aurora DSQL story
    • May 29, 2025
  • 2
    Reliance on US tech providers is making IT leaders skittish
    • May 28, 2025
  • Examine the 4 types of edge computing, with examples
    • May 28, 2025
  • AI and private cloud: 2 lessons from Dell Tech World 2025
    • May 28, 2025
  • 5
    TD Synnex named as UK distributor for Cohesity
    • May 28, 2025
  • Weigh these 6 enterprise advantages of storage as a service
    • May 28, 2025
  • 7
    Broadcom’s ‘harsh’ VMware contracts are costing customers up to 1,500% more
    • May 28, 2025
  • 8
    Pulsant targets partner diversity with new IaaS solution
    • May 23, 2025
  • 9
    Growing AI workloads are causing hybrid cloud headaches
    • May 23, 2025
  • Gemma 3n 10
    Announcing Gemma 3n preview: powerful, efficient, mobile-first AI
    • May 22, 2025
about
Hello World!

We are aster.cloud. We’re created by programmers for programmers.

Our site aims to provide guides, programming tips, reviews, and interesting materials for tech people and those who want to learn in general.

We would like to hear from you.

If you have any feedback, enquiries, or sponsorship request, kindly reach out to us at:

[email protected]
Most Popular
  • Understand how Windows Server 2025 PAYG licensing works
    • May 20, 2025
  • By the numbers: How upskilling fills the IT skills gap
    • May 21, 2025
  • 3
    Cloud adoption isn’t all it’s cut out to be as enterprises report growing dissatisfaction
    • May 15, 2025
  • 4
    Hybrid cloud is complicated – Red Hat’s new AI assistant wants to solve that
    • May 20, 2025
  • 5
    Google is getting serious on cloud sovereignty
    • May 22, 2025
  • /
  • Technology
  • Tools
  • About
  • Contact Us

Input your search keywords and press Enter.