When ATB Financial decided to migrate its vast SAP landscape to the cloud, the primary goal was to focus on things that matter to customers as opposed to IT infrastructure. Based in Alberta, Canada, ATB Financial serves over 800,000 customers through hundreds of branches as well as digital banking options. To keep pace with competition from large banks and FinTech startups and to meet the increasing 24/7 demands of customers, digital transformation was a must. To support this new mandate, in 2019, ATB migrated its extensive SAP backbone to Google Cloud. In addition to SAP S/4 HANA, ATB runs SAP financial services, core banking, payment engine, CRM and business warehouse on Google Cloud. 

In parallel, changes were needed to ATB’s legacy data platform. The platform had stability and reliability issues and also suffered from a lack of historical data governance. Analytics processes were ad hoc and manual. The legacy data environment was also not set up to tackle future business requirements that come with a high dependency on real-time data analysis and insights.

After evaluating several potential solutions, ATB chose BigQuery as a serverless data warehouse and data lake for its next-generation, cloud-native architecture. “BigQuery is a core component of what we call our data exposure enablement platform, or DEEP,” explains Dan Semmens, Head of Data and AI at ATB Financial. According to Semmens, DEEP consists of four pillars, all of which depend on Google Cloud and BigQuery to be successful:

1. Real-time data acquisition: ATB uses BigQuery throughout its data pipeline, starting with sourcing, processing, and preparation, moving along to storage and organization, then discovery and access, and finally consumption and servicing. So far, ATB has ingested and classified 80% of its core SAP banking data as well as data from a number of its third-party partners, such as its treasury and cash management platform provider, its credit card provider, and its call center software. 
2. Data enrichment: Before migrating to Google Cloud, ATB managed a number of disconnected technologies that made data consolidation difficult. The legacy environment could handle only structured data, whereas Google Cloud and BigQuery lets the bank incorporate unstructured data sets, including sensor data, social network activity, voice, text, and images. ATB’s data enrichment program has enabled more than 160 of the bank’s top-priority insights running on BigQuery, including credit health decision models, financial reporting, and forecasting, as well as operational reporting for departments across the organization. Jobs such as marketing campaigns and month-end processes that used to take five to eight hours now run in seconds, saving over CA$2.24 million in productivity. 
3. Self-service analytics: Data for self-service reporting, dashboarding, and visualization is now available for ATB’s 400+ business users and data analysts. Previously, bringing data and analytics to the business users who needed it while ensuring security was burdensome for IT, fraught with recurrent data preparation and other highly manual elements. Now, ATB automates much of its data protection and governance controls through the entire data lifecycle management process. Data access is not only open to more team members but it is faster and easier to acquire without compromising security. And it’s not just raw data that users can access. ATB uses BigQuery to define its enterprise data models and create what it calls its data service layer to make it easier for team members to visualize their data.
4. AI-assisted analytics and automation: Through Google Cloud and BigQuery, ATB has been able to publish data and ML models that provide alerts and notifications via APIs to customer service agents. These real-time recommendations allow customer service agents to provide more tailored service with contextualized advice and suggested new services. So far, the company has deployed more than 40 ML models to generate over 20,000 AI-assisted conversations per month. Thanks to improved customer advocacy and less churn, the bank has realized more than CA$4 million in operating revenue. During the ongoing COVID crisis, the system was also able to predict when business and personal banking customers were experiencing financial distress so that a relationship manager could proactively reach out to offer support, such as payment deferral or loan restructuring. The AI tools provided by BigQuery are also helping ATB detect fraud that previously evaded rules-based fraud detection by using broader sets of timely and accurate data. 

Thanks to the speed and ease of moving data from SAP to BigQuery, ATB is using artificial intelligence (AI) and machine learning (ML) to do things it previously hadn’t thought possible, including sophisticated fraud prevention models, product recommendations, and enriched CRM data that improves the customer experience. 

Using the power of Google Cloud and BigQuery, ATB Financial has been able to draw more value from its SAP data while lowering cost and improving security and reliability. Speed to provide data sets and insights to internal team members has improved 30%. The bank also has seen a 15x reduction in performance incidents while improving data governance and security. Dan Semmens projects that the digital transformation strategy built on Google Cloud and BigQuery has both saved millions compared to its on-premises environment and has also realized millions in new business opportunities. 

Semmens is looking toward the future that includes initiatives like Open Banking and greater ability to provide real time personalized advice for customers to drive revenue growth. “We see our data platform as foundational to ATB’s 10-year strategy,” he says. “The work we’ve undertaken over the past 18 months has enabled critical functionality for that future.” 

Learn more about how ATB Financial is leveraging BigQuery to gain more from SAP data. Visit us here to explore how Google Cloud, BigQuery, and other tools can unlock the full value of your SAP enterprise data.

Road construction is booming in India. A recent report prepared by the India Brand Equity Foundation—a trust established by the Department of Commerce—pointed out that in FY 2019 alone, the country added 10,855 kilometers of highways to a road network that spans 5.89 million kilometers. This network is the second largest in the world and transports 90% of passenger traffic and 64.5% of all goods in the country.

The Indian Government has also earmarked road construction as key to plans to increase the nation’s GDP to $5 trillion in coming years, targeting road construction worth $212.8 billion in the two years from April 2020.

G R Infraprojects Limited is well positioned to support the government’s program. The business, which started as a contractor building roads in rural villages in India, now specializes in road engineering, procurement, and construction (EPC), a model whereby private construction firms build roads funded by the government.

The business now undertakes the processing of bitumen, manufacture of thermoplastic road-marking paint and road signage, and fabrication and galvanizing road-crash barriers. Its in-house integration model includes a design and engineering team, as well as manufacturing facilities in Rajasthan, Assam, and Gujarat.

The business recently expanded into rail—another area expected to benefit from extensive government investment—with its competencies including earthworks, materials supply, track lining, and bridge construction.

In this environment—and despite the economic impact of the coronavirus pandemic—G R Infraprojects Limited aims to substantially increase turnover and manpower over the next five years.

Best-in-class infrastructure key to success

Digital transformation is key to enabling growth while best-in-class IT infrastructure is one of the foundations on which the business seeks to build success.

G R Infraprojects Limited’s digital initiatives include deployment of a new document management system and corporate systems that enable remote monitoring, live tracking, effective real-time communication, and efficient data management.

Providing a scalable, reliable cost-effective infrastructure

But most important of all is providing a scalable, reliable, and cost-effective infrastructure to support a business-critical SAP enterprise resource planning system. Over the last few years, versions of SAP have enabled the organization to digitize processes and seamlessly run business-critical functions such as inventory management and finance.

G R Infraprojects Limited initially went live with SAP ECC6.0, with a few hundred team members using the system for business-critical tasks such as tracking stock level and movement and generating financial statements and reports for review and action.

“Google Cloud is a very big brand, so we were easily able to secure the trust from our executive and business teams to run an important system such as SAP S/4HANA on the platform.”—Sachin Kumar Agarwal, Head, Transformation, G R Infraprojects Limited

Lowering maintenance costs

However, as G R Infraprojects Limited grew, projects proliferated, and new markets emerged, the business elected to move to the cloud from an on-premises infrastructure. “We wanted to move because there were so many maintenance costs in on-premises solutions and cloud provided convenience to IT and the broader organization,” explains Sachin Kumar Agarwal, Head, Transformation at G R Infraprojects Limited.

The business also wanted to move to SAP S/4HANA to take advantage of features such as AI, advanced analytics, and machine learning to transform business processes. The system runs on the HANA database, an in-memory database with fast processing speeds and a simplified data model.

G R Infraprojects Limited selected Google Cloud to run SAP S/4HANA because, Sachin says, it is “much better than any other platform,” incorporates a wide range of features, and meets uptime requirements. The cloud service could also scale to support forecast growth without a sharp increase in cost.

Furthermore, Sachin adds, “Google Cloud is a very big brand, so we were easily able to secure the trust from our executive and business teams to run an important system such as SAP S/4HANA on the platform.”

“With Google Cloud, our speed and availability are controlled and optimized day by day. With such a scalable and dynamic platform, we are very happy with the performance.”—Sachin Kumar Agarwal, Head, Transformation, G R Infraprojects Limited

Successful transition with Infrabeat

G R Infraprojects Limited completed the project with assistance from partner InfraBeat over three months and SAP S/4HANA on Google Cloud went live mid-2019. “Our dedicated SAP team worked closely with Infrabeat to deliver the project successfully,” says Sachin. “We needed an experienced partner to assist with the implementation process and Infrabeat performed that role admirably. Both teams supported each other and worked to plan to deliver a great result.”

SAP S/4HANA runs on an infrastructure comprising virtual machine instances delivered through Compute Engine, Cloud Storage, and Cloud NAT to enable the secure transmission and receipt of packets to and from the internet.

G R Infraprojects Limited estimates the cost of running SAP S/4 HANA in Google Cloud is significantly lower than on alternative infrastructure options—freeing up budget for other business priorities.

In addition, moving SAP S/4 HANA to infrastructure as a service through Google Cloud has eliminated the need to assign internal team members to infrastructure management, allowing them instead to focus on higher-value activities.

Google Cloud also incorporates the security needed to protect the data and processes of SAP S/4 HANA from intrusion or disruption and ensure the uptime and continuity required of a business-critical system.

Optimized speed and availability

G R Infraprojects Limited’s decision to run SAP S/4 HANA on Google Cloud is delivering benefits on a daily basis. “With Google Cloud, our speed and availability are controlled and optimized day by day,” says Sachin. “We are very happy with the performance.”

Success with SAP S/4HANA has helped the business decide to move its remaining apps and data to the cloud when its on-premises servers and other equipment reach end of life. G R Infraprojects Limited is already running Active Directory in Google Cloud and Sachin says the cloud platform’s “fast and excellent services” made the decision easy.

“There are definitely instances of various upgrades of our systems and within the organization, and as we talk about our application and mobility requirements, we see Google Cloud playing a crucial role.”—Sachin Kumar Agarwal, Head, Transformation, G R Infraprojects Limited

Adding value

As G R Infraprojects Limited grows, Sachin adds, the business expects Google Cloud to continue to add value. “There are definitely instances of various upgrades of our systems and within the organization, and as we talk about our application and mobility requirements, we see Google Cloud playing a crucial role.”

Operational resilience continues to be a key focus for financial services firms. Regulators from around the world are refocusing supervisory approaches on operational resilience to support the soundness of financial firms and the stability of the financial ecosystem. Our new white paper discusses the continuing importance of operational resilience to the financial services sector, and the role that a well-executed migration to Google Cloud can play in strengthening it. Here are the key highlights: 

Operational resilience in financial services

Financial services firms and regulators are increasingly focused on operational resilience, reflecting the growing dependency that the financial services industry has on complex systems, automation and technology, and third parties. 

Operational resilience can be defined as the “ability to deliver operations, including critical operations and core business lines, through a disruption from any hazard”¹. Given this definition, operational resilience needs to be thought of as a desired outcome, instead of a singular activity, and as such, the approach to achieving that outcome needs to address a multitude of operational risks including: 

• Cybersecurity: Continuously adjusting key controls, people, processes and technology to prevent, detect and react to external threats and malicious insiders.
• Pandemics: Sustaining business operations in scenarios where people cannot, or will not, work in close proximity to colleagues and customers.
• Environmental and Infrastructure: Designing and locating facilities to mitigate the effects of localised weather and infrastructure events, and to be resilient to physical attacks.
• Geopolitical: Understanding and managing risks associated with geographic and political boundaries between intragroup and third-party dependencies.
• Third-party Risk: Managing supply chain risk, and in particular of critical outsourced functions by addressing vendor lock in, survivability and portability.
• Technology Risk: Designing and operating technology services to provide the required levels of availability, capacity, performance, quality and functionality. 

Operational resilience benefits from migrating to Google Cloud

There is a growing recognition among policymakers and industry leaders that, far from creating unnecessary new risk, a well-executed migration to public cloud technology over the coming years will provide capabilities to financial services firms that will enable them to strengthen operational resilience in ways that are not otherwise achievable.  

Foundationally, Google Cloud’s infrastructure and operating model is of a scale and robustness that can provide financial services customers a way to increase their resilience in a highly commercial way.

Equally important are the Google Cloud products, and our support for hybrid and multi-cloud, that help financial services customers manage various operational risks in a differentiated manner:

• Cybersecurity that is designed in, and from the ground up. From encryption by default, to our Titan security chip, to high-scale DOS defences, to the power of Google Cloud data analytics and Security Command Center our solutions help you secure your environment.
• Solutions that decouple employees and customers from physical offices and premises. This includes zero-trust based remote access that removes the need for complex VPNs, rapidly deployed customer contact center AI virtual agents, and Google Workspace for best-in-class workforce collaboration.
• Globally and regionally resilient infrastructure, data centers and support. We offer a global footprint of 24 regions and 73 zones allowing us to serve customers in over 200 countries, with a globally distributed support function so we can support customers even in adverse circumstances.
• Strategic autonomy through appropriate controls. Our recognition that customers and policymakers, particularly in Europe, strive for even greater security and autonomy is embodied in our work on data sovereignty, operational sovereignty, and software sovereignty.
• Portability, substitutability and survivability, using our open cloud. We understand that from a financial services firm’s perspective, achieving operational resilience may include solving for situations where their third parties are unable, for any reason, to provide the services contracted.
• Reducing technical debt, whilst focusing on great financial products and services. We provide a portfolio of solutions so that financial services firms’ technology organisations can focus on delivering high-quality services and experiences to customers, and not on operating foundational technologies such as servers, networks and mainframes.

Since 2007, PrestaShop has helped companies unlock the power of e-commerce through its open-source platform. Over 300,000 merchants worldwide use the PrestaShop platform to grow their business and serve online shoppers.

“Our open-source strategy to ecommerce enablement sets us apart,” says Rémi Paulin, Ph.D., Data Architect at PrestaShop. “Customization is becoming more crucial to retailers, and our open-source platform allows companies to continually evolve their sites and services to stand out from competitors.”

As PrestaShop grew, it wished to derive more value from its data, but the company ran into issues caused by a legacy, siloed architecture that negatively impacted data consistency and accessibility.

Let’s look at how PrestaShop works with Google Cloud and partners Fivetran and Hightouch to gain more control over data, enable a beyond-BI data strategy, and increase employee engagement from less than 10% to more than 40%.

Improving trust in data

Core systems at PrestaShop, including SQL and NoSQL databases, and SaaS Applications, were siloed; each presenting its own data, often captured from different sources such as support tickets, marketing engagement, purchase activity, and product usage. This setup made data overall inconsistent as no single system would contain a source of truth, resulting in many inefficiencies, poor collaboration across teams, and a reluctance to use data to support key decisions.

“Not long ago, less than 10% of the company regularly relied on data, so we were missing opportunities to make more data-driven decisions,” says Paulin. “Data was underutilized, and people were rapidly losing trust in data.”

PrestaShop set out to design a new architecture to address past challenges, such as lack of data consistency, and improve data accessibility.

“Google Cloud, along with Hightouch and Fivetran, allowed us to build a modern stack to solve these challenges and support our beyond-BI data strategy.”

Building a modern data stack

The first step was to build a robust data ingestion pipeline. After considering several vendors, PrestaShop chose to work with Fivetran to extract data from SaaS applications, including Zendesk, HubSpot, and GitHub, to load into BigQuery. They also use Datastream to stream Change Data Capture (CDC) data from transactional databases into BigQuery in real-time.

“Fivetran and Datastream are no-ops, efficient and highly reliable, and relieve our Data Engineers of management tasks. This brings us a high degree of confidence to build the rest of the stack atop these services,” says Paulin.

PrestaShop relies on several Google Cloud solutions, including Dataflow, and a managed Spark service by Ascend.io, for data transformation. It also uses Looker for its semantic modeling capacities and as a self-serve data platform.

As the company continued on its journey to transform how it manages and benefits from data, it engaged Hightouch to enable data accessibility through activation. Sitting on top of Looker, Hightouch unlocks all data models for operational intelligence. For example, in just a few days, the team built a customer knowledge model combining data from multiple sources and used Hightouch to sync data from the semantic layer to Zendesk via Reverse ETL. This allowed the care team to make more data-informed decisions, speeding up the time to resolve support tickets submitted through Zendesk by 33%.

“Hightouch feels like a natural extension of Looker and reinforces the position of the semantic data model as the single source of truth,” says Paulin. “It powers a variety of Data Activation use cases, supporting our beyond-BI strategy by providing teams with access to data when and where they need it to improve everyday operations. This has a big impact on the company, bolstering employee trust in available data.”

Becoming data-driven

In less than six months, PrestaShop managed to get the entire data stack up and running, build over 30 data models and engage over 120 employees with a small team of only two Data Engineers.

“Data is now accessible to every stakeholder within the company, regardless of their technical abilities,” says Paulin.

PrestaShop has already seen much progress in its shift to a more data-driven company and is excited to roll out more self-service intelligence capabilities in the future.

“Google Cloud drives home a culture of simplicity around our data stack, which is essential for us, especially given the small size of our engineering team,” says Paulin. “Fivetran and Hightouch share this culture of simplicity. Together, they offer strong foundations to support our data needs.”

Dashboards, which the company had always had an appetite for, are seamlessly created today. Before moving to Looker, a full-fledged dashboard would take an average of six weeks to develop. Now, it takes less than two days – and a simple dashboard can be created autonomously by business users in as little as 15 minutes.

Furthermore, data usage goes beyond dashboards. Thanks to Looker’s self-service exploration capabilities, many stakeholders can now glean insights surrounding product issues and business opportunities. Thanks to Hightouch, teams can activate their data to make better and smarter operational decisions.

“This is a big leap forward and one of many to come as we continue to add new models, activate our data, and onboard more users,” says Paulin. “Given our global reach and unique approach to e-commerce enablement, we know this is just the start of the great things we can accomplish with Google Cloud, Fivetran, and Hightouch.”

Check out Fivetran on Google Cloud Marketplace, or sign up for a free Hightouch workspace to learn more about what partners can do for your business.

Compute Engine lets you create and run virtual machines (VMs) on Google’s infrastructure, allowing you to launch large compute clusters with ease. When it comes to getting started with Compute Engine, our customers have lots of questions—but some questions come up more often than others. 

We looked at an internal list of the most popular Compute Engine documentation pages over a 30-day period to find out what topics were explored by users again and again. Here are the top four questions users have about Compute Engine, in order.

1. What are the different machine families

Compute Engine lets you select the right machine for your needs. You can choose from a curated set of predefined virtual machine (VM) configurations optimized for specific workloads, ranging from small-level purpose to large-scale use cases or create a machine type customized to your needs with our custom machine type feature. 

Compute Engine machines are categorized by machine family, including: 

• General-purpose: Best price-performance ratio for a variety of standard and cloud-native workloads 
• Compute-optimized: Highest performance per core for compute-intensive workloads, such as ad serving or media transcoding  
• Memory-optimized: More compute and memory per core than any other family for memory-intensive workloads, such as SAP HANA or in-memory data analytics 
• Accelerator-optimized: Designed for your most demanding workloads, such as machine learning (ML) or high performance computing (HPC)

Read the documentation to learn more about each machine family category.

2. How to connect to VMs using advanced methods

In general, we recommend using the Google Cloud Console and the gcloud command-line tool to connect to Linux VM instances. However, some of our customers want to use third-party tools, or require alternative connection configurations. 

In these cases, there are several methods that might fit your needs better than the standard connection options:

• Connecting to instances using third-party tools (e.g. Windows PuTTY, Chrome OS Secure Shell app), or MacOS or Linux local terminal) 
• Connecting to instances without external IP addresses
• Connecting to instances as the root user Manually connecting between instances and running commands as a service account

Read the documentation to learn about advanced methods for connecting Linux VMs.

3. How to set up OS Login

OS Login lets you use IAM roles and permissions to manage access and permissions to VMs. 

OS Login is the recommended way to manage users across multiple instances or projects. OS Login provides:

• Automatic Linux account lifecycle management
• Fine-grained authorization using Google IAM without having to grant broader privileges
• Automatic permissions updates to prevent unwanted access
• Ability to import existing Linux accounts from Active Directory (AD) and Lightweight Directory Access Protocol (LDAP)

You can also add an extra layer of security by setting up OS Login with two-factor authentication or manage organization access by setting up organization policies.

Read the documentation to learn how to configure OS login and connect to your instances.

4. How to manage SSH keys in metadata 

Compute Engine allows you to manually manage SSH keys and local user accounts by editing public SSH key metadata.

You can add  public SSH keys to instance and project metadata using: 

• The Google Cloud Console The gcloud command-line tool 
• API methods from the Google Cloud Client Libraries

Read the documentation to learn how to manually manage SSH keys and local user accounts in metadata.

Don’t see your question here? Check out the Compute Engine documentation for all of our recommended guides, tutorials, and resources.