As retailers strive to meet the growing expectations of shoppers, they are turning to Google Cloud to transform their businesses and tackle opportunities in an increasingly challenging industry. From optimizing inventory management to increasing collaboration between employees across locations and roles, to helping build omnichannel experiences for their customers, we are working together with retailers to help make the shopping experience as seamless and personalized as possible.  

A standout Google Cloud customer is Macy’s, one of the world’s largest retailers. Founded in 1858, Macy’s operates approximately 680 Macy’s and Bloomingdale’s, and 190 specialty stores including Bloomingdale’s The Outlet, Bluemercury and Macy’s Backstage. And through macys.com, bloomingdales.com, and bluemercury.com, it also serves millions of customers across more than 100 countries. 

By moving its infrastructure to the cloud, and taking advantage of Google Cloud data warehousing and analytics solutions, Macy’s is streamlining retail operational functions across its network.

With the opening of its new approximately 675,000 square-foot distribution center in Columbus, Ohio, Macy’s is leveraging the scalability of Google Cloud to ensure that merchandise is accurately and efficiently received, sorted, ticketed, picked, packed and shipped from the distribution center to the stores—even during peak retail seasons like back to school and the holidays.

“Powered by software developed at Macy’s technology, this new distribution center is a fantastic first step in our cloud journey. Working with Google Cloud allows us to be more nimble, efficient and flexible in how we utilize our warehouses,” 

Naveen Krishna, CTO, Macy’s

Leveraging Google Cloud’s data management and analytics solutions, Macy’s new warehouse management system will initially service 200+ Macy’s Backstage off-price stores at launch. Macy’s will begin rolling out this software solution to additional distribution centers that service its nationwide fleet of Macy’s and Bloomingdale’s department stores, as well as Macys.com and Bloomingdales.com direct-to-customer orders. 

Our continued work with Macy’s reflects their investment in technology to improve digital and mobile experiences, site stability, store technology, fulfillment, and logistics, and integrate its front line and back office to reinvent retail. I look forward to deepening our partnership with Naveen and his team to help them achieve these goals. 

🎧 Prefer to listen? Check out this episode on the Google Cloud Reader podcast

If you’re anything like me, you love reading, but also appreciate that sometimes your eyes need to be doing other things; whether it’s finding your exit off the highway, or keeping your puppy from destroying the couch.

And sometimes the thought of sitting down to read something just feels like it’s going to take valuable multi-tasking time away from my day. I know, I know, multitasking can be frowned upon, but it’s the way I live a good chunk of my life, and it’s working out so far. And while I’m not alone in my multitasking, I’m also not alone in my desire for a non-visual way to get this content, or any content.

*Google Cloud Reader enters the chat*

Google Cloud Reader is a podcast that lets you listen to the Google Cloud Blog posts that aren’t as dependent on visuals. This means they’re articles that are, or are adapted to be, less focused on graphs, or code samples, and instead describe the meaning behind those visual aids. 

It’s an easy, audible way to absorb content around all things new in Cloud, while still being able to make sure Ruthie doesn’t eat my work from home equipment. 

So by now you’re probably thinking “OK, so you started a podcast during the pandemic, even though you definitely seemed like the type to start making sourdough”—and you’re right. My 53 plants agree with you. But rest assured, one can listen to an episode of this podcast *while* creating a macramé plant hanger, or waiting for bread to rise—multitasking, am I right?

We’re a little over 50 episodes/macrame plant hangers in, so you should check it out (Ruth and I would appreciate it).

Some of my personal favorites 

• Beginners Guide to Painless Machine Learning – Learn how to get started with Google Cloud AI tools
• Introducing GKE Autopilot: A Revolution in Managed Kubernetes – Learn more about GKE Autopilot, a revolutionary mode of operations for managed Kubernetes that lets you focus on your software, while GKE Autopilot manages the infrastructure.
• Cook up your own ML recipes with AI Platform – ​​Learn about Mars Wrigley’s new ML-inspired recipe experiment on Google Cloud and how you can get started with your own.
• Recovering Global Wildlife Populations using ML – Review Google’s Wildlife Insight’s ML project and help users create an image classification model for motion-sensor cameras (called camera traps) used to help protect wildlife in an non-invasive way by collecting and tagging species via pictures.

Let me know your favorite episodes, and what other articles you’d like to hear on Twitter @jbrojbrojbro!

No matter why you prefer an audio format, we’ve got you covered; Google Cloud Reader, where we read the tech blog for you, and to you.

Get all the Google Cloud Reader on your favorite podcast platform, including Google Podcasts, Apple Podcasts, and Spotify.

In our conversations with technology leaders about data-driven transformation using Google Data Cloud –  industry’s leading unified data and AI solution – , one important topic is incorporating continuous intelligence to move from answering questions such as “What has happened? to questions like “What is happening?” and “What might happen?”. The core to this evolution is the need for an underlying data processing that not only provides powerful real-time capabilities for events happening close to origination, but also brings together existing data sources under one unified data platform to enable organizations to draw insights and take actions holistically. Dataflow, Google’s cloud-native data processing and streaming analytics platform, is a key component of any modern data and AI architecture and data transformation journey, along with BigQuery, Google’s internet-scale warehouse with built-in streaming, BI engine and ML; Pub/Sub, a global no-ops event delivery service; and Looker, a modern BI and embedded analytics platform. One of the key evaluation factors is potential economic value of Dataflow to their organization, particularly in the context of engaging other stakeholders is key for many of the leaders that we engage with. So we commissioned Forrester Consulting to conduct a comprehensive study on the impact that Dataflow had on their organization by interviewing actual customers . 

Today we’re excited to share our commissioned study conducted by Forrester Consulting, the Total Economic Impact™ of Google Cloud Dataflow, which allows data leaders to understand and quantify the benefits of Dataflow, and use cases it enables. Forrester conducted interviews with Dataflow customers to evaluate the benefits, costs, and risks of investing in Dataflow across an organization. Based on their interviews, Forrester identified major financial benefits across four different areas: business growth, infrastructure cost savings, data engineer productivity, and administration efficiency. In fact, Forrester found that customers adopting Dataflow can achieve a 55% boost in developer productivity and a 50% reduction in infrastructure costs. In fact, Forrester projects that customers adopting Dataflow can achieve a range of up to 171% Return on Investment (ROI) and a less than six months payback period. Customers can now use figures in the report to compute their own Return on Investment (ROI) and payback period.

“Dataflow is integral to accelerating time-to-market, decreasing time-to-production, reducing time to figure out how to use data for use cases, focusing time on value-add tasks, streamlining ingestion, and reducing total cost of ownership.” – Lead technical architect, CPG

Let’s take a deeper look at the ways that Forrester found that Dataflow can help you achieve your goals and unlock your business potential. 

Benefit #1: Increase data engineer productivity by 55%

Developers can choose among a variety of programming languages to define and execute data workflows. Dataflow also seamlessly integrates with other Google Cloud Platform and open source technologies to maximize value and applicability to a wide variety of use cases. Dataflow streamlined workflows with code reusability,dynamic templates, and the simplicity of a managed service. Engineers trusted pipelines to run correctly and adhere to governance. Data engineers avoided laborious issue-monitoring and remediation tasks that were common in the legacy environments such as poor performance, lack of availability, and failed jobs. Teams valued the language flexibility and open source base.

“Dataflow provided us with ETL replacement that opened limitless potential use cases and enabled us to do smarter data enhancement while data remains in motion.” — Director of data projects, financial services

Benefit #2: Reduce infrastructure costs by up-to 50% for batch and streaming workloads 

Dataflow’s serverless autoscaling and discrete control of job needs, scheduling, and regions eliminated overhead and optimized technology spending. Consolidating global data processing solutions to Dataflow further eliminated excess costs while ensuring performance, resilience, and governance across environments. Dataflow’s unified streaming and batch data platform gives organizations the flexibility to define either workload in the same programming model, run it on the same infrastructure, and manage it from a single operational management tool. 

“Our costs with our cloud data platform using Dataflow are just a fraction of the costs we faced before. Now we only pay for cloud infrastructure consumption because the open source base helps us avoid licensing costs. We spend about $120,000 per year with Dataflow, but we’d be spending millions with our old technologies.” – Lead technical architect, CPG

Benefit #3: Increase top-line revenue by improving customer experience and retention with payback time of < 6 months

Streaming analytics is an essential capability in today’s digital world to gain real-time actionable insights. Likewise, organizations must also have flexible, high- performance batch environments to analyze historical data for building machine learning models, business intelligence, and advanced analytics. Dataflow enabled real-time streaming use cases, improved data enrichment, encouraged data exploration,improved performance and resiliency, reduced errors, increased trust, and eliminated barriers to scale. As a result, organizations provided customers with more accurate, relevant, and in-the-moment data-backed services and insights — boosting customer experience, creating new revenue streams, and improving acquisition, retention, and enrichment.

“It’s already been proven that we are getting more business [with Dataflow] because we can turn around results faster for customers.” – VP of technology, financial services technology

“When we provide data to our customers and partners with Dataflow, we are much more confident in those numbers and can provide accurate data within a minute. Our customers and partners have taken note and commented on this. It’s reduced complaints and prevented churn.” – Senior software engineer, media

Other benefits 

Eliminated administrative overhead and toil

As a cloud-native managed service, all administration tasks such as provisioning, scaling, and updates are automatically handled by Google Cloud. Teams no longer need to manage servers and related software for legacy data processing solutions. Admins also streamlined processes for setting up data sources, adding pipelines, and enforcing governance.

Saved business operations costs for support teams and data end users

Dataflow improved the speed, quality, reliability, and ease of access to data for insights for general business users, saving time and empowering users to drive better data-backed outcomes. It also reduced support inquiry volume while automating manual job creation.

What’s next?

Download the Forrester Total Economic Impact study today to dive deep into the economic impact Dataflow can deliver your organization. We would love to partner with you to explore the potential Dataflow can unlock in your teams. Please reach out to our sales team to start a conversation about your data transformation with Google Cloud.