If You Run Your Country’s Largest Retail Franchise, How Do You Pull Together, in Sync?
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In 1984, Mario Maio set up a small business manufacturing electrical transformers in his Johannesburg garage. Over the next two decades, the ACDC Dynamics company he created came to dominate manufacturing, import, and distribution in South Africa’s electrical goods sector. Then, in 2007, Mario’s son, Ricardo Maio, founded a retail arm to the business, ACDC Express. Today ACDC Express is South Africa’s largest electrical retail franchise, with 29 franchise stores across the country. Eight of those franchises joined in 2017 alone, and ACDC Express is experiencing quarter-on-quarter growth of 28% per year.
Rapid expansion increases the demands on the ACDC Express central administration, which provides each franchise with IT support and a full suite of marketing, operational, and bookkeeping functions. So when email server downtime became a frequent problem, Ricardo and his team chose G Suite to transform the way the franchise worked.
“We lost revenue when our email servers went down. When I researched Google’s SLA of 99.9% uptime and experimented with G Suite on my private Gmail account, I could see the difference this technology could create.”
Ricardo Maio, CEO, ACDC Express
“On consecutive occasions, our entire email server went down,” says Ricardo Maio, CEO at ACDC Express. “It would take more than one or two days to bring it back up. We had already highlighted software cost overhead as a potential thing to reduce, so when that happened several times within a short period, we knew it was time to make a change.”
Building a better franchise
Franchise businesses undergoing rapid expansion must respond quickly to the demands of new stores. At ACDC Express, 33 staff run the national franchise, delivering core services and support to 29 franchises across the country. Key tasks, such as updating the operations manual, were hampered by a reliance on paper forms and mail services, while email servers experienced repeat failures, which compromised communication. By implementing new, cloud-based productivity tools, ACDC Express looked to cut down on slow and expensive practises, and deliver an agile, reliable online communications platform.
To do that, ACDC Express migrated its franchise to G Suite with Opennetworks. “We lost revenue when our email servers went down,” says Ricardo. “When I researched Google’s SLA of 99.9% uptime and experimented with G Suite on my private Gmail account, I could see the difference this technology could create.”
Since moving to Gmail, ACDC Express reports that the problem of email server downtime “is no longer existent for us,” while with Google Drive, versioning problems have been resolved. Using surveys on Google Forms, ACDC Express quickly and easily collects data from stores and customers—whether they are in stores or on the road—and populates Google Sheets with the information.
“Our operations manual is a binding document, and it’s a living document that gets regularly updated. In the past, we would struggle to track which franchise had which version. With Google Drive, we can be sure that everyone is looking at the right one.”
Ricardo Maio, CEO, ACDC Express
With Google Data Studio, the managing team then consolidates that data on dashboards, creating snapshots of performance, complete with averages and simple comparisons, which make it easy to spot issues and outliers in need of attention. Individual businesses that do require help are then contacted over Google Hangouts Meet to assess what they need, part of a culture of sharing expertise, which Ricardo sees as key to the franchise mode.
“As a franchise, sharing knowledge is as important as maintaining control,” he says. “If there’s a new procedure or system that worked in one store, we can immediately update our manuals and documentation so that everyone has access to it. That’s been fantastic.”
“Our operations manual is a binding document, and it’s a living document, which gets regularly updated,” says Ricardo. “In the past, we would struggle to track which franchise had which version, and every time we had to make a change we would print out a version and send it to stores through an unreliable postal service. With Google Drive, we can be sure that everyone is looking at the right one.”
Remote training, rapid migration
Rolling out new IT tools across a franchise is often expensive, demanding extensive travel and numerous training sessions, which often repeat the same material. Instead, ACDC Express set up training on Google Hangouts that staff could drop into at their convenience, creating a cost-effective training schedule, which meant individual stores could plan their own learning process.
“When we moved to G Suite, we did it all at once, with every employee changing at the same time. We took a band-aid approach, switching to the new tools as rapidly as possible. After six months of training, there have been no reported problems with G Suite at all.”
Ricardo Maio, CEO, ACDC Express
“The whole benefit of franchising is that you can learn from your peers,” says Ricardo. “When we moved to G Suite, we did it all at once, with every employee changing at the same time. We took a band-aid approach, switching to the new tools as rapidly as possible. After six months of training, there have been no reported problems with G Suite at all.”
More mobile, more reliable
Today, ACDC Express operates 240 Google accounts, and information from the franchises’ marketing systems, research, operations, and accounting is fed back automatically to Google Sheets and Google Dashboard at the headquarters in Edenvale, Gauteng. By Ricardo’s estimation, the administrative team is now so effective with G Suite tools, it can achieve twice as much as it could without them.
Now, ACDC Express is looking to use Google Chromebooks in a new web-based point-of-sale system, and considering moving its ERP onto Google Cloud Platform for greater stability, in another project with Opennetworks.
“We’ve developed an in-house point of sale system that’s web-based and can use a functional touchscreen,” adds Ricardo. “We’re looking at rolling that out with Google Chromebooks. We really like how straightforward and simple the Google Chrome devices are, and because we’ve taken a lot of infrastructure into the cloud, we no longer actually need physical machines on our counters. We can work anywhere. That’s something that applies from our head office right down to our smallest franchise store.”
Google Cloud’s Data Analytics May Recap
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May was a very busy month for data analytics product innovation. If you didn’t have the chance to attend our inaugural Data Cloud Summit, video replays of all our sessions are now available so feel free to watch them at your own pace.
In this blog, I’d like to share some background behind the innovations we released in May, why we built them the way we did, and the type of value they can bring your company and your team.
But first, a huge thank you!
This week, we had the honor to announce that Google has been named a Leader in The Forrester Wave™: Streaming Analytics, Q2 2021 report. Forrester gave Dataflow a score of 5 out of 5 across 12 different criteria, stating: “Google Cloud Dataflow has strengths in data sequencing, advanced analytics, performance, and high-availability”.
Google has more than a decade of experience in building real-time and internet-scale systems for its own needs, and we are excited to see that our ability to provide customers with a reliable, scalable, and performant platform is bearing fruit.
This announcement comes on the back of the release of The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report, which also named Google Cloud as a Leader.
We couldn’t be more excited about the recognition and appreciate all your feedback and trust in the work that we do to support your goal in accelerating data-powered innovation.
Innovation galore
Your feedback and your passion is the fuel that drives our ambition to deliver more and better services to you. That’s why, this year, we didn’t want to wait until Google Cloud Next to share some great products we have been working on. On May 26, our team announced a slew of new products, services and programs. Watch a quick summary below:
https://youtube.com/watch?v=DG1mOPMXJvw%3Fenablejsapi%3D1%26
Meeting you where you are
An important design principle behind all of our services is “meeting you where you are”. This means we aim to provide you with the tools and software you need to innovate on your own terms. Here are three new services that will help you do just that:
Datastream
Datastream, our new serverless change data capture (CDC) and replication service, allows your company to synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency to support real-time analytics, database replication, and event-driven architectures. Datastream delivers change streams from Oracle and MySQL databases into Google Cloud services such as BigQuery, Cloud SQL, Cloud Storage, and Cloud Spanner, saving time and resources while ensuring your data is accurate and up-to-date.
- Under the hood, Datastream reads CDC events (inserts, updates, and deletes) from source databases, and writes those events with minimal latency to a data destination. It leverages the fact that each database source has its own CDC log—binlog for MySQL and LogMiner for Oracle—which it uses for its own internal replication and consistency purposes.
- Datastream integrates with purpose-built and extensible Dataflow templates to pull the change streams written to Cloud Storage, and create up-to-date replicated tables in BigQuery for analytics. It also leverages Dataflow templates to replicate and synchronize databases into Cloud SQL or Cloud Spanner for database migrations and hybrid cloud configurations.
- Datastream also powers a Google-native Oracle connector in Cloud Data Fusion’s new replication feature for easy ETL/ELT pipelining. By delivering change streams directly into Cloud Storage, customers can leverage Datastream to implement modern, event-driven architectures.
Looker and BigQuery Omni on Microsoft Azure
Research on multi cloud adoption is unequivocal — 92% of businesses in 2021 report having a multi cloud strategy. We want to continue supporting your choice by providing the flexibility you need to see your strategy through.
- This past month, we introduced Looker, hosted on Microsoft Azure. For the first time, you can now choose Azure, Google Cloud, or AWS for your Looker instance. You can also self-host your Looker instance on-premises.
- We also introduced BigQuery Omni for Azure, which along with last year’s introduction of BigQuery Omni for AWS, will help you access and securely analyze data across Google Cloud, AWS, and Azure.
The cost of moving data between cloud providers isn’t sustainable for many, and it’s still difficult to seamlessly work across clouds. BigQuery Omni represents a new way of analyzing data stored in multiple public clouds, which is made possible by BigQuery’s separation of compute and storage. By decoupling these two, BigQuery provides scalable storage that can reside in Google Cloud or other public clouds, and stateless resilient compute that executes standard SQL queries.
- Unlike competitors, BigQuery Omni doesn’t require you to move or copy your data from one public cloud to another, where you might incur egress costs. You also benefit from the same BigQuery interface on Google Cloud, enabling you to query data stored in Google Cloud, AWS, and Azure without any cross-cloud movement or copies of data.
- BigQuery Omni’s query engine runs the necessary compute on clusters in the same region where your data resides. For example, you can query Google Analytics 360 Ads data stored in Google Cloud and query logs data from your ecommerce platform and applications that are stored in AWS S3 and/or Microsoft Azure.
Then, using Looker, you can build a dashboard that allows you to visualize your audience behavior and purchases alongside your advertising spend.
Dataplex
We understand that most organizations still struggle to make high-quality data easily discoverable and accessible for analytics, across multiple silos, to a growing number of people and tools within their organization.
They are often forced to make tradeoffs. For instance, moving and duplicating data across silos to enable diverse analytics use cases or leaving their data distributed but limiting the agility of decisions.
- Dataplex provides an intelligent data fabric that enables you to centrally manage, monitor, and govern your data across data lakes, data warehouses, and data marts, while also ensuring data is securely accessible to a variety of analytics and data science tools.
- One of the core tenets of Dataplex is letting you organize and manage your data in a way that makes sense for your business, without data movement or duplication. For that, we provide logical constructs like lakes, data zones, and assets. These constructs enable you to abstract away the underlying storage systems and become the foundation for setting policies around data access, security, lifecycle management, and so on.
- For example, you can create a lake per department within your organization (e.g. Retail, Sales, Finance, etc.) and create data zones that map to data readiness and usage (e.g. landing, raw, curated_data_analytics, curated_data_science, etc.).
Once you have your lakes and zones setup, you can attach data to these zones as assets. You can add data from different types of storage (e.g. GCS Bucket and BigQuery dataset) under the same zone. You can also attach data across multiple projects under the same zone. You can ingest data into your lakes and zones using the tools of your choice, including services such as Dataflow, Data Fusion, Dataproc, Pub/Sub, or choose from one of our partner products. Dataplex comes with built-in 1-click templates for common data management tasks.
To find out more about Dataplex, head to cloud.google.com/dataplex or watch the video below:
https://youtube.com/watch?v=bbFeAt7cw1g%3Fenablejsapi%3D1%26
Helping you innovate everyday
Sharing data is hard. Traditional data sharing techniques use batch data pipelines that are expensive to run, create late arriving data, and can break with any changes to the source data. These techniques also create multiple copies of data, which brings unnecessary costs and can bypass data governance processes. They also fail to offer features for data monetization, such as managing subscriptions and entitlements. Altogether, these challenges mean that organizations are unable to realize the full potential of transforming their business with shared data.
Analytics Hub
To address these limitations, we are introducing Analytics Hub, a new fully managed service that helps organizations unlock the value of data sharing, leading to new insights and increased business value.
This new service is built on the tremendous experience and feedback we have received over the years. For example, BigQuery has had cross-organizational, in-place data sharing capabilities since its inception in 2010—and the functionality is very popular. Over a 7-day period in April, we had over 3,000 different organizations sharing over 200 petabytes of data. These numbers don’t include data sharing between departments within the same organization.
Analytics Hub takes sharing to the next level, making it easy for you to publish, discover, and subscribe to valuable datasets that you can combine with your own data to derive unique insights.
This includes:
- Shared datasets: As a data publisher, you create shared datasets that contain the views of data that you want to deliver to your subscribers. Data subscribers can search through the datasets that are available across all exchanges for which they have access and subscribe to relevant datasets. In addition, the publisher can track subscribers, disable subscriptions, and see aggregated usage information for the shared data.
- Curated, self-service data exchanges: Exchanges are collections used to organize and secure shared datasets. By default, exchanges are completely private, but granular roles and permissions make it easy to deliver data to the right audience—whether internal or public.
This is just the beginning for Analytics Hub. Please sign up for the preview, which is scheduled to be available in the third quarter of 2021.
Dataflow Prime
At Google Cloud, we have the great privilege of working with some of the most innovative organizations in the world. And this work provides us with a unique perspective into the future of big data processing. Dataflow Prime is a new platform based on a serverless, no-ops, and auto-tuning architecture that brings unparalleled resource utilization and radical operational simplicity to big data processing. This new service introduces a large number of exciting capabilities but I’d like to highlight three key aspects of the product:
- Vertical Autoscaling: Dataflow Prime dynamically adjusts the compute capacity allocated to each worker based on utilization, detecting when jobs are limited by worker resources and automatically adding more resources. Vertical Autoscaling works hand in hand with Horizontal Autoscaling to seamlessly scale workers to best fit the needs of the pipeline. As a result, it no longer takes hours or days to determine the perfect worker configuration to maximize utilization.
- Right Fitting: Each stage of a pipeline typically has a different resource requirement than the others. Until now, either all workers in the pipeline would have had the higher memory and GPU, or none of them would. Pipelines either had to waste resources or suffer slower workloads. Right Fitting solves this problem by creating stage-specific pools of resources, optimized for each stage.
- Smart Recommendations: Smart Recommendations automatically detects problems in your pipeline and shows potential fixes. For example, if your pipeline is running into permissions issues, a Smart Recommendation will detect which IAM permissions you need to enable to unblock your job. If you are using an inefficient coder in your job, Smart Recommendations will surface more performant coder implementations that can help you save on costs.
What’s next
We’re excited to hear your thoughts and feedback about all these exciting new services. I would also highly recommend that you connect with members of the community to learn more about their story and journey. A good example to start with is the Data To Value customer panel we produced at our inaugural Data Cloud Summit with the Chief Data Officers of Keybank and Rackspace. You can watch it for free below:
https://youtube.com/watch?v=ITI2Q3MkxuA%3Fenablejsapi%3D1%26
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The Inside Story of How Home Depot Migrated to Google BigQuery From an On-prem DW Solution
In the media, you will often hear story of how born-in-the-cloud companies manage with massive infrastructure.
But it is one thing is to be a startup, and build infrastructure with bespoke requirements. And quite another to have a complex, multinational organization with online, with mobile, with brick-and-mortar presence, and hundreds of thousands of SKUs and professional services, and many, many years of technology, innovation, and really smart engineers.
This is the second story. The story of how The Home Depot, the number-one home improvement retailer in the US pulled of that feat.
The Home Depot has over 2,200 stores, over 4 lakh associates, and 2017 revenues of over a $100 billion.
In this video, Rick Ramaker, technology director, data analytics at The Home Depot, and Kevin Scholz, distinguished engineer, The Home Depot, talk about how the company transformed and modernised its data warehousing, the challenges they faced and the benefits they accrued from the project.
It’s a fascinating watch!
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The Transformative Journeys of Financial Firms on Google Cloud: Watch Video
The reliance on cloud-based architectures, high performance computing, big data and more are accelerating in the banking, capital, insurance and financial services industries. Google Cloud had a strong role in transforming many businesses especially in the pandemic to smoothly transition into the digital space and understand their customers. Two years since then, financial firms have been able to design better products based on intelligent, real-time insights and leverage many capabilities of Google Cloud to deliver tailored experiences. So, how big of an impact Google Cloud has on the future of the financial services? The answer is huge and endless.
Watch this video to dive into the state of global financial services companies that leveraged modern cloud architecture for their sensitive data, platforms, devices and products while they increase revenues, stay compliant and curb costs.
New Enterprise Capabilities and Changes to Cloud Spanner Reduces Cost of Running Workloads by 90 Percent
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Customers love Cloud Spanner because it gives them the benefits of relational semantics and SQL while also delivering the scale and availability of non-relational databases. Many of these customers want to move even more of their work to Spanner, and have requested smaller instance sizes to support development, testing and small production workloads. We’re happy to announce that they’ll soon get what they asked for: more granular instance sizing is coming to Spanner.
Granular instance sizing will be available in Public Preview soon. With this feature, you can run workloads on Spanner at as low as 1/10th the cost of regular instances, equating to approximately $65/month.
In addition, we are launching new enterprise capabilities to break down operational silos for real-time insights and provide greater database observability to developers:
- Datastream, now in public preview, is a change data capture (CDC) service that allows enterprises to synchronize data across heterogeneous databases and applications. With Spanner support in Datastream, users will be able to stream data from MySQL or Oracle to Spanner reliably and with minimal latency.
- BigQuery federation to Spanner (coming soon) lets users query transactional data residing in Spanner, from BigQuery, without moving or copying data.
- Key Visualizer, available now in public preview, provides interactive monitoring so developers can quickly identify trends and usage patterns in Spanner.
Democratizing access with more granular instance sizing
Today, customers provision Spanner instances by specifying the number of nodes they need to run their workloads. Each node can provide up to 10,000 queries per second (QPS) of reads or 2,000 QPS of writes (writing single rows at 1 KB of data per row) and 2 TB of storage. A Spanner node is replicated across 3 zones for regional instances, and 5 or more zones for multi-regional instances. The choice of node count determines the amount of serving and storage resources that are available to the databases in a given instance.
Historically, the most granular unit for provisioning resources on Spanner has been one node. To enable more granular control, we are introducing Processing Units (PUs); one Spanner node is equal to 1,000 PUs. Customers can now provision in batches of 100 PUs, and get a proportionate amount of compute and storage resources. This will allow teams to run smaller workloads on Spanner at much lower cost. With this feature, customers can start at 100 PUs and scale up as needed in batches of 100 PUs, to up to 1,000 PUs (1 node), all with zero downtime. Subsequently, customers can continue to scale up by adding more nodes, just like what they do today. Customers do have the choice of using either PUs or nodes to provision resources within workloads, when those workloads occupy multiple nodes of capacity.
To illustrate with an example, let’s say a game developer creates a Spanner instance called “baseball-game” in us-central1, with 100 PU compute capacity at $65/month price.
As you can see below, proportional maximum storage of 205 GB is assigned to the 100 PU instance.
Once the game starts becoming popular and resource demands increase, the user edits the instance to increase the compute capacity to 500 PUs with proportional maximum 1 TB of storage.
The game grows in popularity, and the gaming company prepares to launch a much-awaited capability in the game. Anticipating a sharp increase in usage at launch day, the game developers increase the compute capacity to 3,000 PUs. Compute capacity assigned to the instance over a period of time can be viewed in Cloud Monitoring graphs:
Request Access
You can request early access to granular instance sizing feature by filling this form.
Breaking down operational silos with Datastream CDC and BigQuery federation
BigQuery Federation. BigQuery has made analytics easy by bringing together data from multiple sources for seamless analysis. Soon you’ll also be able to analyze data in Spanner directly in BigQuery. With Spanner’s BigQuery federation, you’ll be able to instantly query data residing in Spanner in real-time without moving or copying the data. Simply set up the Spanner as an external data source in BigQuery, as shown below.
Change Data Capture ingest. Now in public preview, Datastream lets you stream change data into Google Cloud from MySQL and Oracle databases. As of today, you can ingest this change data directly into Spanner using a built-in Dataflow template. This lets you migrate data from MySQL and Oracle databases into Spanner in near-real time.
Understanding performance and resource usage with Key Visualizer
Key Visualizer is a new interactive monitoring tool that lets developers and administrators analyze usage patterns in Spanner. It reveals trends and outliers in key performance and resource metrics for databases of any size, helping to optimize queries and reduce infrastructure costs. Designed for performance tuning and instance sizing, Key Visualizer is available today in public preview in the web-based Cloud Console for all Spanner databases at no additional cost. Learn more in the Key Visualizer blog.
Learn more
- To request early access to granular instance sizing in Spanner, fill out this form.
- To get started with Spanner today, create an instance or try it out with a Spanner Qwiklab.
ATB Financial Focuses on Customer Experience with the Speed it Gains in the Cloud
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As senior vice president and head of technology enablement for ATB Financial, Barry Hensch has a mission: creating a seamless experience for the Alberta, Canada-based bank’s nearly 800,000 customers by leveraging the latest digital technology. ATB is a purpose-driven financial institution owned and operated by Alberta’s provincial government, with about C$55.1 billion in assets under management between its banking and wealth-management arms. The full-service bank also boasts a large market share of small businesses in the province.
As part of ATB’s drive to meet its customers’ ever growing expectations, Hensch has embarked on an ambitious digital transformation strategy, migrating the bank’s vast SAP infrastructure onto Google Cloud. The move takes hardware capacity and maintenance concerns entirely off his plate so he and his team can pursue innovations that bring true value to the customer.
Hensch recently discussed ATB’s cloud journey, the new capabilities the cloud has opened up for ATB, and where the company plans to go using Google Cloud’s artificial intelligence and machine learning capabilities.
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