google big data case study pdf

Big Data Case Studies

• First Online: 13 June 2018

Cite this chapter

• Butch Quinto 2  

2800 Accesses

Big data has disrupted entire industries. Innovative use case in the fields of financial services, telecommunications, transportation, health care, retail, insurance, utilities, energy, and technology (to mention a few) have revolutionized the way organizations manage, process, and analyze data.

• Apache Spark
• Cloudera Manager
• Hadoop Components
• Apache Hive

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and affiliations.

Plumpton, Victoria, Australia

Butch Quinto

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Butch Quinto

About this chapter

Quinto, B. (2018). Big Data Case Studies. In: Next-Generation Big Data. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3147-0_13

Download citation

DOI : https://doi.org/10.1007/978-1-4842-3147-0_13

Published : 13 June 2018

Publisher Name : Apress, Berkeley, CA

Print ISBN : 978-1-4842-3146-3

Online ISBN : 978-1-4842-3147-0

eBook Packages : Professional and Applied Computing Professional and Applied Computing (R0) Apress Access Books

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

8 case studies and real world examples of how Big Data has helped keep on top of competition

Fast, data-informed decision-making can drive business success. Managing high customer expectations, navigating marketing challenges, and global competition – many organizations look to data analytics and business intelligence for a competitive advantage.

Using data to serve up personalized ads based on browsing history, providing contextual KPI data access for all employees and centralizing data from across the business into one digital ecosystem so processes can be more thoroughly reviewed are all examples of business intelligence.

Organizations invest in data science because it promises to bring competitive advantages.

Data is transforming into an actionable asset, and new tools are using that reality to move the needle with ML. As a result, organizations are on the brink of mobilizing data to not only predict the future but also to increase the likelihood of certain outcomes through prescriptive analytics.

Here are some case studies that show some ways BI is making a difference for companies around the world:

1) Starbucks:

With 90 million transactions a week in 25,000 stores worldwide the coffee giant is in many ways on the cutting edge of using big data and artificial intelligence to help direct marketing, sales and business decisions

Through its popular loyalty card program and mobile application, Starbucks owns individual purchase data from millions of customers. Using this information and BI tools, the company predicts purchases and sends individual offers of what customers will likely prefer via their app and email. This system draws existing customers into its stores more frequently and increases sales volumes.

The same intel that helps Starbucks suggest new products to try also helps the company send personalized offers and discounts that go far beyond a special birthday discount. Additionally, a customized email goes out to any customer who hasn’t visited a Starbucks recently with enticing offers—built from that individual’s purchase history—to re-engage them.

2) Netflix:

The online entertainment company’s 148 million subscribers give it a massive BI advantage.

Netflix has digitized its interactions with its 151 million subscribers. It collects data from each of its users and with the help of data analytics understands the behavior of subscribers and their watching patterns. It then leverages that information to recommend movies and TV shows customized as per the subscriber’s choice and preferences.

As per Netflix, around 80% of the viewer’s activity is triggered by personalized algorithmic recommendations. Where Netflix gains an edge over its peers is that by collecting different data points, it creates detailed profiles of its subscribers which helps them engage with them better.

The recommendation system of Netflix contributes to more than 80% of the content streamed by its subscribers which has helped Netflix earn a whopping one billion via customer retention. Due to this reason, Netflix doesn’t have to invest too much on advertising and marketing their shows. They precisely know an estimate of the people who would be interested in watching a show.

3) Coca-Cola:

Coca Cola is the world’s largest beverage company, with over 500 soft drink brands sold in more than 200 countries. Given the size of its operations, Coca Cola generates a substantial amount of data across its value chain – including sourcing, production, distribution, sales and customer feedback which they can leverage to drive successful business decisions.

Coca Cola has been investing extensively in research and development, especially in AI, to better leverage the mountain of data it collects from customers all around the world. This initiative has helped them better understand consumer trends in terms of price, flavors, packaging, and consumer’ preference for healthier options in certain regions.

With 35 million Twitter followers and a whopping 105 million Facebook fans, Coca-Cola benefits from its social media data. Using AI-powered image-recognition technology, they can track when photographs of its drinks are posted online. This data, paired with the power of BI, gives the company important insights into who is drinking their beverages, where they are and why they mention the brand online. The information helps serve consumers more targeted advertising, which is four times more likely than a regular ad to result in a click.

Coca Cola is increasingly betting on BI, data analytics and AI to drive its strategic business decisions. From its innovative free style fountain machine to finding new ways to engage with customers, Coca Cola is well-equipped to remain at the top of the competition in the future. In a new digital world that is increasingly dynamic, with changing customer behavior, Coca Cola is relying on Big Data to gain and maintain their competitive advantage.

4) American Express GBT

The American Express Global Business Travel company, popularly known as Amex GBT, is an American multinational travel and meetings programs management corporation which operates in over 120 countries and has over 14,000 employees.

Challenges:

Scalability – Creating a single portal for around 945 separate data files from internal and customer systems using the current BI tool would require over 6 months to complete. The earlier tool was used for internal purposes and scaling the solution to such a large population while keeping the costs optimum was a major challenge

Performance – Their existing system had limitations shifting to Cloud. The amount of time and manual effort required was immense

Data Governance – Maintaining user data security and privacy was of utmost importance for Amex GBT

The company was looking to protect and increase its market share by differentiating its core services and was seeking a resource to manage and drive their online travel program capabilities forward. Amex GBT decided to make a strategic investment in creating smart analytics around their booking software.

The solution equipped users to view their travel ROI by categorizing it into three categories cost, time and value. Each category has individual KPIs that are measured to evaluate the performance of a travel plan.

Reducing travel expenses by 30%

Time to Value – Initially it took a week for new users to be on-boarded onto the platform. With Premier Insights that time had now been reduced to a single day and the process had become much simpler and more effective.

Savings on Spends – The product notifies users of any available booking offers that can help them save on their expenditure. It recommends users of possible saving potential such as flight timings, date of the booking, date of travel, etc.

Adoption – Ease of use of the product, quick scale-up, real-time implementation of reports, and interactive dashboards of Premier Insights increased the global online adoption for Amex GBT

5) Airline Solutions Company: BI Accelerates Business Insights

Airline Solutions provides booking tools, revenue management, web, and mobile itinerary tools, as well as other technology, for airlines, hotels and other companies in the travel industry.

Challenge: The travel industry is remarkably dynamic and fast paced. And the airline solution provider’s clients needed advanced tools that could provide real-time data on customer behavior and actions.

They developed an enterprise travel data warehouse (ETDW) to hold its enormous amounts of data. The executive dashboards provide near real-time insights in user-friendly environments with a 360-degree overview of business health, reservations, operational performance and ticketing.

Results: The scalable infrastructure, graphic user interface, data aggregation and ability to work collaboratively have led to more revenue and increased client satisfaction.

6) A specialty US Retail Provider: Leveraging prescriptive analytics

Challenge/Objective: A specialty US Retail provider wanted to modernize its data platform which could help the business make real-time decisions while also leveraging prescriptive analytics. They wanted to discover true value of data being generated from its multiple systems and understand the patterns (both known and unknown) of sales, operations, and omni-channel retail performance.

We helped build a modern data solution that consolidated their data in a data lake and data warehouse, making it easier to extract the value in real-time. We integrated our solution with their OMS, CRM, Google Analytics, Salesforce, and inventory management system. The data was modeled in such a way that it could be fed into Machine Learning algorithms; so that we can leverage this easily in the future.

The customer had visibility into their data from day 1, which is something they had been wanting for some time. In addition to this, they were able to build more reports, dashboards, and charts to understand and interpret the data. In some cases, they were able to get real-time visibility and analysis on instore purchases based on geography!

7) Logistics startup with an objective to become the “Uber of the Trucking Sector” with the help of data analytics

Challenge: A startup specializing in analyzing vehicle and/or driver performance by collecting data from sensors within the vehicle (a.k.a. vehicle telemetry) and Order patterns with an objective to become the “Uber of the Trucking Sector”

Solution: We developed a customized backend of the client’s trucking platform so that they could monetize empty return trips of transporters by creating a marketplace for them. The approach used a combination of AWS Data Lake, AWS microservices, machine learning and analytics.

• Reduced fuel costs
• Optimized Reloads
• More accurate driver / truck schedule planning
• Smarter Routing
• Fewer empty return trips
• Deeper analysis of driver patterns, breaks, routes, etc.

8) Challenge/Objective: A niche segment customer competing against market behemoths looking to become a “Niche Segment Leader”

Solution: We developed a customized analytics platform that can ingest CRM, OMS, Ecommerce, and Inventory data and produce real time and batch driven analytics and AI platform. The approach used a combination of AWS microservices, machine learning and analytics.

• Reduce Customer Churn
• Optimized Order Fulfillment
• More accurate demand schedule planning
• Improve Product Recommendation
• Improved Last Mile Delivery

How can we help you harness the power of data?

At Systems Plus our BI and analytics specialists help you leverage data to understand trends and derive insights by streamlining the searching, merging, and querying of data. From improving your CX and employee performance to predicting new revenue streams, our BI and analytics expertise helps you make data-driven decisions for saving costs and taking your growth to the next level.

Most Popular Blogs

Elevating User Transitions: JML Automation Mastery at Work, Saving Hundreds of Manual Hours

Smooth transition – navigating a seamless servicenow® upgrade, seamless integration excellence: integrating products and platforms with servicenow®.

TechEnablers Episode 4: Transforming IT Service Managem

TechEnablers Episode 3: Unlocking Efficiency: Accelerat

TechEnablers Episode 2: POS Transformation: Achieving S

Navigating the Future: Global Innovation, Technology, a

Revolutionizing Retail Supply Chains by Spearheading Di

Navigating the Digital Transformation Journey in the Mo

AWS Named as a Leader for the 11th Consecutive Year…

Introducing amazon route 53 application recovery controller, amazon sagemaker named as the outright leader in enterprise mlops….

• Made To Order
• Cloud Solutions
• Salesforce Commerce Cloud
• Distributed Agile
• IT Strategy & Consulting
• Data Warehouse & BI
• Security Assessment & Mitigation
• Case Studies

Quick Links

• Privacy Statement
•   +91-22-61591100
•   [email protected]

• Español – América Latina
• Português – Brasil

BQ: Powering mobile innovation

BQ is one of the leading technology companies in Europe that designs and develops consumer electronics such as smartphones, 3D printers, and robotics. The company’s philosophy is to make technology a tool for improving the world and the lives of its users. More than 170 engineers work on BQ devices from conceptual design and mechanics to hardware and software development, production, and the QA process. BQ sells its mobile devices to more than 5 million customers in over 40 countries.

Tell us your challenge. We're here to help.

Using google kubernetes engine and bigquery on google cloud, bq is providing better service at a lower cost, helping increase its time to market over much larger manufacturers., google cloud results:.

• Scaled to support more than a 2,000% increase in services with Google Kubernetes Engine on Google Cloud
• Able to thrive and grow in a competitive market
• Saved 60% in cloud hosting costs

Easily managed jump from 15 to 350 services

Travel most anywhere in the world and you’ll see people using smartphones for work, for play, and to stay connected with friends and family. As global demand for mobile technologies continues to soar, smartphone manufacturing has become an ultra-competitive business dominated by highly visible, global brands.

Just a few years ago, the idea that a small European company could compete with industry giants seemed unlikely, but that’s exactly what BQ did. The company realized that many people in Spain felt that they were paying too much for their phones and offered cost-conscious consumers what they wanted: excellent service and high-quality devices at a more affordable price.

The strategy worked, and demand for BQ products and services increased significantly across Europe. The company also found new ways to grow, becoming one of the top three 3D printer manufacturers in Europe. Suddenly, BQ went from providing services to several thousand local customers to having to provide reliable service and updates to millions of devices—a challenge difficult to manage using an IT infrastructure built on individual virtual machines.

“By moving to Google Cloud and Kubernetes Engine, we were able to scale quickly from 15 services to 350 services while reducing our cloud hosting costs by approximately 60%.”

To scale quickly, BQ began migrating services to Docker containers running on Google Kubernetes Engine —built on the open source Kubernetes system. With Kubernetes Engine, BQ has a managed orchestration platform for Kubernetes to keep its small team focused on innovation rather than IT maintenance.

“Since we moved to Kubernetes Engine on Google Cloud , our development is much easier,” says Pablo Moncada, IT DevOps Team Lead, at BQ. “There is no extra work for our team in having to manage our extensive environment, allowing us to ship faster and to focus on more strategic projects.”

Better service at a lower cost with Google Cloud

In addition to streamlining management, BQ wanted to reduce costs while maintaining high availability. Google Cloud helped solve both problems.

By using preemptible (highly affordable, short-lived) Compute Engine instances with automated container management for fault tolerance, BQ gets the best of both worlds: highly affordable compute instances and high availability. It can, therefore, operate at a significantly lower cost and provide better service to customers and employees. Instead of running each cloud service on a separate node, BQ now runs 350 services on just 20 nodes.

“The combination of Google Workspace and Google Cloud empowers our small team of engineers to effectively serve BQ’s employees around the world.”

The company also relies on Cloud SQL , which provides fully managed database services, freeing BQ engineers from operational tasks and performance optimization. With the help of Cloud SQL, the company’s engineers can improve development cycles and gain more time to work on projects that provide value to its customers.

“By moving to Google Cloud, we were able to scale from 15 services to 350 services while reducing our cloud hosting costs by approximately 60%,” says Pablo. “A team of three engineers is all we need to keep our environment running smoothly. Without Google Cloud, we would need three times as many people.”

Rich insights with BigQuery

BQ also uses BigQuery to quickly analyze information from millions of devices and application logs. Engineers and product development teams can then visualize metrics with Tableau and build custom reports and dashboards using Looker Studio and glean valuable insights that influence product development and customer services.

“We are constantly improving product quality based on user experience data analyzed with BigQuery. For example, we can tell if a hardware component such as an antenna is affecting smartphone performance, or understand how a software update is impacting battery life,” says Pablo. “To gather this intelligence, we query across multiple databases containing large stores of data, which would be impossible to do cost effectively without BigQuery.”

“With its expertise in a rapidly evolving technology landscape, Google is the perfect match for us in a world that demands constant improvement in services. Our goals align nicely with Google. We want to empower people with the right tools to work and play their best.”

Transparent and connected with Google Workspace

From day one, BQ built its business processes around Google Workspace , using Google Drive for an open, central storage platform; Google Sheets , Docs , and Calendar for transparent collaboration; Gmail for fast email searches and reliable message delivery; and Google Meet to maximize staff contact while saving on travel, video conferencing, and telecom costs overall.

“The combination of Google Workspace and Google Cloud empowers our small team of engineers to effectively serve BQ’s employees around the world,” says Pablo. “There’s instant, reliable collaboration between our teams worldwide. The Google Workspace products are especially optimized for mobile use, so any employee at any time can effectively communicate product challenges or opportunities that we can address to ensure continued delivery of world-class services.”

Staying one step ahead

With Google Cloud and Google Workspace, BQ can increase its market share and pave the way for future innovations. The company regularly collaborates with Google’s Android team and is currently testing the AI and machine learning products with the goal of enhancing its products with artificial intelligence.

“With its expertise in a rapidly evolving technology landscape, Google is the perfect match for us in a world that demands constant improvement in services,” adds Pablo. “Our goals align nicely with Google. We want to empower people with the right tools to work and play their best.”