Dataplex: Google Cloud’s Intelligent Data Fabric to Manage Data and Analytics at Scale
4866
Of your peers have already read this article.
2:30 Minutes
The most insightful time you'll spend today!
Enterprises are struggling 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—to move and duplicate data across silos to enable diverse analytics use cases or leave their data distributed but limit the agility of decisions.
Today we are excited to announce Dataplex, an intelligent data fabric that provides a way to centrally manage, monitor, and govern your data across data lakes, data warehouses and data marts, and make this data securely accessible to a variety of analytics and data science tools.
Dataplex provides an integrated analytics experience, bringing together the best of Google Cloud and open source tools, so you can rapidly curate, secure, integrate, and analyze data at scale. With built-in data intelligence using Google Artificial Intelligence (AI) and machine learning (ML) capabilities and a flexible consumption model, you can now spend less time wrestling with infrastructure and more time focused on driving business outcomes.
Dataplex enables you to:
- Achieve freedom of choice to store data wherever you want for the right price/performance and choose the best analytics tools for the job, including Google Cloud and open source analytics technologies such as Apache Spark and Presto.
- Enforce consistent controls across your data to ensure unified security and governance
- Take advantage of the built-in data intelligence using Google’s best in class AI/ML capabilities to automate much of the manual toil around data management and get access to higher quality data.
Early customers like Equifax, Loblaw, and ANZ are excited about using Dataplex to address data management complexity.
“Dataplex will greatly simplify the existing analytics workflows within Equifax with its unified data fabric and single interface for policy management and governance across all our analytics data. Its built-in data discovery and data quality features will ensure that our data scientists and analysts always have access to high quality data that they can trust. Dataplex aligns well with our enterprise data strategy and we are excited to partner with Google Cloud on this.”
—Kumar Menon, SVP, Data Fabric & Decision Science Technology, Equifax.
“Loblaw is Canada’s food and pharmacy leader, and we are excited to be an early adopter of Dataplex. We could significantly benefit from Dataplex as it provides a single pane of glass for end-to-end data management and governance. We are particularly interested in improving platform resilience and data quality by detecting anomalies as early as possible in the data pipeline with the help of Dataplex.”
—Elton Martins, Senior Director of Data Insights & Analytics, Loblaw
“We are undergoing a major data transformation at ANZ, bringing together our various data assets and building a cohesive data ecosystem for customer benefit. Dataplex’s vision and capabilities align well with our current data strategy to build a unified data fabric for all our analytics and AI/ML use cases. We are excited to partner with GCP on Dataplex and test the product in private preview.”
—Ashish Shekhar, Head of Technology – Enterprise Analytics & Applied AI, ANZ
Dataplex is built for distributed data. We are starting with data stored in Google Cloud Storage and BigQuery, with support for other data sources coming soon. It provides a workflow-driven experience helping you build an open data platform and make data easily accessible to your end users while ensuring your policies and best practices are consistently enforced.
Organizing and curating your data
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 are providing logical constructs like lakes, data zones and assets. Those 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 (Retail, Sales, Finance, etc.) and create data zones that map to data readiness and usage (landing, raw, curated_data_analytics, curated_data_science, etc.).
Once you have your lakes and zones setup, you can now 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 provides built-in 1-click templates for common data management tasks.
Securing your data
Dataplex enables you to define and enforce consistent policies across your data, irrespective of where it physically resides. Data owners can easily set up policies for specific data domains based on business needs, without thinking about where the data is stored while data stewards get global visibility into governance policies and permissions across their data.
You can apply security and governance policies for your entire lake, a specific zone, or an asset. Dataplex maps the policies to the underlying storage and pushes down permissions to the storage layer to provide end-to-end secure data access. Additionally, you can secure not just data but also related artifacts like notebooks, scripts, and models using the same set of access policies.
Making high quality data available for analytics and data science
One of the biggest differentiators for Dataplex is our data intelligence capabilities using Google’s best in class AI/ML technologies. As you bring the data under management, Dataplex will automatically harvest the metadata for both structured and unstructured data, with built-in data quality checks. All of the metadata is automatically registered in a unified metastore, and made available for search and discovery. It is also published to Bigquery, Dataproc Metastore, and Data Catalog – ensuring that you have the same consistent data context and access across your tools.
For example, when you write parquet files to a Google Cloud Storage bucket – Dataplex will automatically extract metadata of these files, detect a tabular schema, including hive-style partitions, run data quality checks, and make this data queryable in BigQuery as an external table and from any open source or partner application – with the same consistent security and access policies you defined at the logical data layer.
Your data scientists and analysts now have secured access to this data that meets your quality bar and governance rules via the tools of their choice, without needing any additional processing.
One-click access to collaborative analytics
Dataplex provides fully managed, one-click analytics environments enabling you to use the power of Apache Spark and BigQuery with support for other engines coming in the future.
As data administrators, you now have the flexibility to pre-configure these environments with the right cost and financial governance measures without taking on the overhead of managing and maintaining the infrastructure required to power these environments. You can easily configure different environments for different types of workloads and share it with multiple users using their IAM credentials. Dataplex manages the provisioning, monitoring, scaling, and shutdown of these environments.
As data scientists, analysts, and engineers, you now have a turn-key experience to run your analysis using notebooks and a SQL workbench. You can search for notebooks and scripts alongside data, save and share your work with other users, and schedule your notebooks or scripts for recurring workloads – all using the same integrated experience within Dataplex.
Building an open platform with industry leaders
We are partnering with industry leaders such as Accenture, Collibra, Confluent, Informatica, HCL, Starburst, NVIDIA, Trifacta, and others to build an open platform to power analytics at scale. Our partners are excited about the capabilities that Dataplex will provide:
“Collibra is excited to partner with Dataplex to provide data governance and data quality for consistent controls across distributed data. Pairing Collibra’s multi-cloud and hybrid solution with Dataplex allows enterprises to securely open up access to more, higher quality data for users and analytics using a single unified view.”
—Jim Cushman, Chief Product Officer, Collibra
“Dataplex builds on Google Cloud’s commitment to open source by integrating with Apache Kafka®, a leading open source platform for event streaming. We at Confluent, the platform for data in motion that completes Apache Kafka® to be enterprise-ready, are excited to partner with Dataplex to enable customers to bring together distributed, real-time data and build a unified data fabric for end to end analytics.”
—Paul Mac Farland, VP, Head of Customer Solutions and Innovation, Confluent
“We are excited to partner with Google Cloud’s Dataplex team as we look to provide our joint customers an integrated and open data fabric for analytics at scale. Extending Dataplex’s data management and data quality capabilities with Starburst Enterprise will accelerate time to value for enterprises looking to connect distributed data without having to move data.”
—Justin Borgman, CEO and Co-founder, Starburst
Next Steps
Dataplex is now available in preview for a select number of customers. For more information, visit our website or watch the recording. If you would like to sign up, please click here.
How Google Cloud and SAP Address Global Supply Chain Initiatives
3517
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
With SAP Sapphire kicking off today in Orlando, we’re looking forward to seeing our customers and discussing how they can make core processes more efficient and improve how they serve their customers.
One thing is certain to be top of mind – the global supply chain challenges facing the world today. It’s affecting every business across every industry, from common household items that once filled store shelves and are now on backorder, to essential goods and services like food and medical treatments, which are at risk. Even cloud-native companies are making changes to ensure they have the insights, equipment, and other assets they need to continue serving customers.
We are proud to work with SAP on many initiatives that are driving results for our customers and helping them run more intelligent and sustainable companies. I’d like to highlight three of these important initiatives and how they are helping address global supply chain challenges.
Enabling more efficient migrations of critical workloads
We know a key barrier to entry in the cloud is the ability to easily migrate from on-premises environments. Our cloud provides a safe path to help companies including Johnson Controls, PayPal, and Kaeser Compressor to digitize and solve large, complex business problems, reduce costs, scale without cycles of investment, and gain access to key services and capabilities that can unlock value and enable growth.
Singapore-based shipping company Ocean Network Express (ONE) has become more agile by running their mission-critical SAP workloads on Google Cloud and using our data analytics to improve operational efficiency and make faster decisions. They have gone from an on-premises data warehouse solution that would take a full day loading data from SAP S/4HANA, to using our BigQuery solution that delivers business insights in minutes.
Since The Home Depot moved its critical SAP workloads to Google Cloud, the company has been able to shorten the time it takes to prepare a supply chain use case from 8 hours to 5 minutes by using BigQuery to analyze large volumes of internal and external data. This helps improve forecast accuracy and more effectively replenish inventory by being able to create a new plan when circumstances change unexpectedly with demand or a supplier.
Accelerating cloud benefits through RISE and LiveMigration
At Google Cloud, we have dedicated programs to help migrate SAP and other mission-critical workloads to our cloud with our Cloud Acceleration Program for SAP.
For SAP customers moving to Google Cloud, we provide LiveMigration to provide superior uptime and business continuity. LiveMigration eliminates downtime required for planned infrastructure maintenance. This means that your SAP system continues running even when Google Cloud is performing planned infrastructure maintenance upgrades thus ensuring superior business continuity for your mission critical workloads.
We are also proud to be a strategic partner with the RISE with SAP program, which helps accelerate cloud migration for SAP’s global customer base while minimizing risks along the migration journey. This program provides solutions and expertise from SAP and technology ecosystem partners to help companies transform through process consulting, workload migration services, cloud infrastructure, and ongoing training and support. To secure your mission critical workloads, SAP and Google Cloud can provide a 99.9% uptime SLA as part of the RISE with SAP program.
Many large manufacturers have taken advantage of RISE with SAP to forge a secure, proven path to our cloud, including Energizer Holdings Inc., a leading manufacturer and distributor of primary batteries, portable lights, and auto care products. Energizer has turned to RISE with SAP on Google Cloud to power its move to SAP S/4HANA. The company wants to automate essential business processes, improve customer service, and boost innovation. It had been using a private cloud solution but needed to gain flexibility while better containing costs.
“SAP S/4HANA for central finance will help us automate essential business processes, improve customer service, and fuel innovation that grows our company’s leadership position globally. We selected RISE with SAP to begin our journey to SAP S/4HANA and maintain the freedom and flexibility to move at our own pace,” said Energizer Chief Information Officer Dan McCarthy.
Another example is global automotive distributor Inchcape, which moved its mission-critical sales, marketing, finance, and operations systems and data to Google Cloud. With its diverse data sets now in a single, secure cloud platform, Inchcape is applying Google Cloud AI and ML capabilities to manage and analyze its data, automate operations, and ultimately transform the car ownership experience for millions.
“Google Cloud’s close relationship with SAP and its strong technical expertise in this space were a big pull for us,” said Mark Dearnley, Chief Digital Officer at Inchcape. “Ultimately, we wanted a headache-free RISE with SAP implementation and to unlock value for auto makers and consumers in all our regions, while continuing to have the choice and flexibility to modernize our 150-year old business in a way that works for us.”
A new intelligence layer for all SAP Google Cloud customers
When moving mission-critical workloads to the cloud, companies not only need to migrate safely, they also need to quickly realize value, which we enable with Google Cloud Cortex Framework — a layer of intelligence that integrates with SAP Business Technology Platform (SAP BTP). Google Cloud Cortex Framework provides reference architectures, deployment accelerators, and integration services for analytics scenarios.
Like many large e-commerce companies, Mercado Libre experienced skyrocketing transactions that more than doubled in 2020 as people sheltered at home during the pandemic, and they are anticipating more growth. The Google Cloud Cortex Framework is enabling Mercado Libre to respond, run more efficiently, and make faster, data-driven decisions.
Continued partnership to support organizations around the world
Our longstanding partnership with SAP continues to yield exciting innovations for our customers, and we’re honored to work with them to help customers address the ongoing impact of global supply chain challenges. We’re looking forward to sharing new insights and innovations at SAP Sapphire this week, and to listening and learning from you about your plans and challenges, and how we can best support your transformation to the cloud.
Forrester Study Finds 72% ROI from Moving Expensive, Traditional OS and Software to Google Cloud!
DOWNLOAD RESEARCH REPORTS3181
Of your peers have already downloaded this article
20:00 Minutes
The most insightful time you'll spend today!
Google Cloud commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examined the potential return on investment (ROI) for companies that have migrated to Google Cloud. The study evaluates the risks, benefits and costs associated with Google Cloud migration and the experiences of five customers with large, expensive on-prem infrastructure and workload operating on legacy operating systems. The results and impacts of interviewed customers are combined into a single composite organization. The findings reveal that customers incurred 72 percent ROI and annual software savings worth 2.2 million USD within three years of migrating expensive software operating systems and traditional software to Google Cloud!
Download the study report to gain a detailed understanding of migrating on-prem infrastructure to cloud to attain business velocity, innovation, adaptability and better customer experiences with Google Cloud!
5546
Of your peers have already downloaded this article
1:30 Minutes
The most insightful time you'll spend today!
Security in public clouds differs intrinsically from customer-owned infrastructure because there is shared responsibility for security between the customer and the cloud provider.
Cloud Security is different from on-premises security because of the combination of the following:
- Differences in security primitives, visibility, and control points within the infrastructure, products
- and services.
- New cloud-native development methodologies like containerization and DevSecOps.
- The continued velocity and variety of new cloud products and services and how they can be
- consumed.
- Cultural shifts in how organizations deploy, manage, and operate systems.
Here is a Google Cloud Security Foundations Guide to help you develop a security blueprint for your cloud deployments.
Pacemaker’s Automated Alerts and Alert Reporting: No More Outages for SAP Systems on Google Cloud!
3265
Of your peers have already read this article.
6:00 Minutes
The most insightful time you'll spend today!
When critical services fail, businesses risk losing revenue, productivity, and trust. That’s why Google Cloud customers running SAP applications choose to deploy high availability (HA) systems on Google Cloud.
In these deployments Linux operating system clustering provides application and guest awareness for the application state and automates recovery actions in case of failure — including cluster node, resource or node failover or failed action.
Pacemaker is the most popular software Linux administrators use to manage their HA clusters, which includes automating notifications about events — including failover fencing and node, attribute, and resource events — and reporting on events. With automated alerts and reports, Linux administrators can not only learn about events as they happen, but they can also make sure other stakeholders are alerted to take action when critical events occur. They can even discover past events to assess the overall health of their HA systems.
Here, we break down the steps to setting up automated alerts for HA cluster events and alert reporting.
How to Deploy the Alert Script
To set up event-based alerts, you’ll need to take the following steps to execute the script.
1. Download the script file ‘gcp_crm_alert.sh’ from
https://github.com/GoogleCloudPlatform/pacemaker-alerts-cloud-logging
2. Under root user, add exec flag for the script and execute deployment with:
chmod +x ./gcp_crm_alert.sh./gcp_crm_alert.sh -d
3. Confirm that the deployment runs successfully. If it does, you will see the following INFO log messages:
In the Red Hat Enterprise Linux (RHEL) system:
gcp_crm_alert.sh:2022-01-24T23:48:30+0000:INFO:'pcs alert recipient add gcp_cluster_alert value=gcp_cluster_alerts id=gcp_cluster_alert_recepient options value=/var/log/crm_alerts_log' rc=0
In the SUSE Linux Enterprise Server (SLES):
gcp_crm_alert.sh:2022-01-25T00:13:27+00:00:INFO:'crm configure alert gcp_cluster_alert /usr/share/pacemaker/alerts/gcp_crm_alert.sh meta timeout=10s timestamp-format=%Y-%m-%dT%H:%M:%S.%06NZ to { /var/log/crm_alerts_log attributes gcloud_timeout=5 gcloud_cmd=/usr/bin/gcloud }' rc=0Now, in the event of a cluster node, resource, node failover, or failed action, Pacemaker will start the alert mechanism. For further details on the alerting agent, check out the Pacemaker Explained documentation.
How to Use Cloud Logging for Alert Reporting
Alerted events are published in Cloud Logging. Below is an example of the log record payload, where the cluster alert key-value pairs get recorded in the jsonPayload node.
{
"insertId": "ktildwg1o3fbim", "jsonPayload": { "CRM_alert_recipient": "/var/log/crm_alerts_log", "CRM_alert_attribute_name": "", "CRM_alert_kind": "resource", "CRM_alert_status": "0", "CRM_alert_rsc": "STONITH-sapecc-scs", "CRM_alert_rc": "0", "CRM_alert_timestamp_usec": "", "CRM_alert_interval": "0", "CRM_alert_node_sequence": "21", "CRM_alert_task": "start", "CRM_alert_nodeid": "", "CRM_alert_timestamp": "2022-01-25T00:17:06.515313Z", "CRM_alert_timestamp_epoch": "", "CRM_alert_desc": "ok", "CRM_alert_target_rc": "0", "CRM_alert_version": "1.1.15", "CRM_alert_attribute_value": "", "CRM_alert_node": "sapecc-ers", "CRM_alert_exec_time": "" }, "resource": { "type": "global", "labels": { "project_id": "gcp-tse-sap-on-gcp-lab" } }, "timestamp": "2022-01-25T00:17:09.662557309Z", "severity": "INFO", "logName": "projects/gcp-tse-sap-on-gcp-lab/logs/sapecc-ers%2F%2Fvar%2Flog%2Fcrm_alerts_log", "receiveTimestamp": "2022-01-25T00:17:09.662557309Z" }
To get notified of a resource event — for example, when the HANA topology resource monitor fails — you can use the following filter for the alerting definition:
jsonPayload.CRM_alert_node=("hana-venus" OR "hana-mercury") -jsonPayload.CRM_alert_status="0" jsonPayload.CRM_alert_rsc="rsc_SAPHanaTopology_SBX_HDB00" jsonPayload.CRM_alert_task="monitor" To define an alert for a fencing event, your can apply this filter: jsonPayload.CRM_alert_node=("hana-venus" OR "hana-mercury") jsonPayload.CRM_alert_kind="fencing" The fencing log entry gets recorded with warning severity to give you deeper insight, and this additional information is also helpful for more specific filtering criteria: { "insertId": "1plznskfjsxt82", "jsonPayload": { "CRM_alert_attribute_value": "", "CRM_alert_recipient": "/var/log/crm_alerts_log", "CRM_alert_rsc": "", "CRM_alert_rc": "0", "CRM_alert_timestamp_usec": "529261", "CRM_alert_desc": "Operation reboot of hana-mercury by hana-venus for crmd.2361@hana-venus: OK (ref=2a9bf814-9adf-4247-af3f-94ac254fc3ca)", "CRM_alert_target_rc": "", "CRM_alert_nodeid": "", "CRM_alert_kind": "fencing", "CRM_alert_node_sequence": "33", "CRM_alert_task": "st_notify_fence", "CRM_alert_status": "", "CRM_alert_exec_time": "", "CRM_alert_attribute_name": "", "CRM_alert_timestamp_epoch": "1643072786", "CRM_alert_version": "1.1.19", "CRM_alert_timestamp": "2022-01-25T01:06:26.529261Z", "CRM_alert_interval": "", "CRM_alert_node": "hana-mercury" }, "resource": { "type": "global", "labels": { "project_id": "gcp-tse-sap-on-gcp-lab" } }, "timestamp": "2022-01-25T01:06:27.267017052Z", "severity": "WARNING", "logName": "projects/gcp-tse-sap-on-gcp-lab/logs/hana-venus%2F%2Fvar%2Flog%2Fcrm_alerts_log", "receiveTimestamp": "2022-01-25T01:06:27.267017052Z"
} Alerts can be delivered through multiple channels, including text and email. Below is an example of an email notification for our earlier example, when we defined an alert for a HANA topology resource monitor failure:
You can write and apply filters to your log-based alerts to isolate certain types of incidents and analyze events over time. For example, the following script will surface a resource event occurring within a two-hour window on a specific date:
timestamp>="2022-01-25T00:00:00Z" timestamp<="2022-01-25T02:00:00Z"
jsonPayload.CRM_alert_kind="resource"
With the ability to analyze these logged alerts over time, determine whether event patterns warrant any action.
[SIDEBAR]
The alert script prints details in the standard output and in the log file /var/log/crm_alerts_log, and this can grow over time. We recommend that the log file is set with the Linux logrotate service in order to limit the file system space. Use the following command to create the necessary logrotate setting for the alerting log file:
cat > /etc/logrotate.d/crm_alerts_log << END-OF-FILE /var/log/crm_alerts_log { create 0660 root root rotate 7 size 10M missingok compress delaycompress copytruncate dateext dateformat -%Y%m%d-%s notifempty } END-OF-FILE [END SIDEBAR]
Tips for Troubleshooting When you first deploy your alert script, how can you tell for certain that you’ve done it correctly? Use the following commands to test it out:
In RHEL:
pcs alert show
In SLES:
sudo crm config show | grep -A3 gcp_cluster_alert
You should see the following if the script is correct:
In RHEL:
Alerts: Alert: gcp_cluster_alert (path=/usr/share/pacemaker/alerts/gcp_crm_alert.sh) Description: "Cluster alerting for hana-node-X" Options: gcloud_cmd=/usr/bin/gcloud gcloud_timeout=5 Meta options: timeout=10s timestamp-format=%Y-%m-%dT%H:%M:%S.%06NZ Recipients: Recipient: gcp_cluster_alert_recepient (value=gcp_cluster_alerts) Options: value=/var/log/crm_alerts_log In SLES:
alert gcp_cluster_alert "/usr/share/pacemaker/alerts/gcp_crm_alert.sh" \ meta timeout=10s timestamp-format="%Y-%m-%dT%H:%M:%S.%06NZ" \ to "/var/log/crm_alerts_log" attributes gcloud_timeout=5 gcloud_cmd="/usr/bin/gcloud" If the commands do not display the alerts properly, re-deploy the script.
In case there is an issue with the script, or if the Cloud Logging records are not presenting as expected, examine the script log file /var/log/crm_alerts_log. The errors and warning can be filtered with:
egrep '(ERROR|WARN)' /var/log/crm_alerts_log
Any Pacemaker alert failures will be recorded in the messages and/or Pacemaker log. To examine recent alert failures, use the following command:
egrep '(gcp_crm_alert.sh|gcp_cluster_alert)' \ /var/log/messages /var/log/pacemaker.log
Keep in mind, though, that the Pacemaker log location may be different in your system from the one in the example above.
From reactive to proactive
Your SAP applications are too critical to risk outages. The most effective way to manage high availability clusters for your SAP systems on Google Cloud is to take full advantage of Pacemaker’s alerting capabilities, so you can be proactive in ensuring your systems are healthy and available.
Learn more about running SAP on Google Cloud.
Home Depot’s Interconnected Retail Experience by Virtue of Google Cloud Migration for SAP Applications
8285
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
With nearly 2,300 stores, The Home Depot is the world’s largest home-improvement chain — a brand that professional contractors and DIYers alike have come to depend on. The home improvement industry continues to experience unprecedented demand and dramatic increases in online ordering accompanied by expanding consumer expectations for things like curbside pickup and same day delivery. The Home Depot’s decision to migrate to cloud-based infrastructure, including the migration of the company’s SAP applications on Google Cloud which began in 2017, has set it up for success in an increasingly digital world, and helped the company adapt to changing market conditions quickly.
Interconnected retail at scale
Building on a strong customer-first philosophy, The Home Depot aims to create what it calls interconnected retail—allowing customers to shop however, whenever, and wherever they want. “So many companies are focused on omni-channel retail,” explains Sam Moses, Vice President of Corporate Systems. “At The Home Depot, we wanted to take it to the next level. Interconnected retail puts the customer at the center of everything and enables them to shop in store, online, or both. Customers can begin a transaction online and continue in-store, or vice-versa.”
To support this strategy, the company’s SAP environment needed to be more agile. Running everything on-premises, from central finance to POS systems, meant that The Home Depot’s IT teams experienced redundancy and repetitive, manual processes. Their data warehouse needed an upgrade to process and analyze growing and increasingly diverse data sets. The Home Depot chose to migrate its SAP environment to Google Cloud to support both the velocity and scale needed for the business as well as critical analytics capabilities needed for its bold digital initiatives. “We chose Google Cloud to support our SAP implementation. Our decision had a lot to do with the relationship between Google Cloud and SAP and also for the applications and services that are offered by Google Cloud, like BigQuery, which are helping to enable data and analytics within our organization,” Moses explains.
After migrating its SAP applications—including S/4HANA, its customer activity repository (CAR), general ledger, e-commerce system, enterprise data warehouse and more to Google Cloud, the company now has the speed, scale and flexibility to tackle enormous spikes in the business, all while staying fully available for their customers. Additionally, The Home Depot was able to transform its financial systems and make them more agile to deliver critical information across multiple business functions in real time.
Maximizing data insights to support customer experiences
By migrating to Google Cloud, The Home Depot is leveraging Google Cloud analytics to build the industry’s most efficient supply chain including more robust demand forecasting, supplier lead times, estimated delivery times and more, all while maintaining better security than before. “We experienced unprecedented change in our customers’ behavior and their buying patterns, which puts a lot of pressure on our supply chain,” explains Moses. “So having the ability to leverage data and analytics gives us insights to know exactly what it is that our customers need.”
The company’s analysts now use BigQuery ML for machine learning directly against the company’s BigQuery data and use AutoML to determine the best model for predictions. The Home Depot’s engineers have also adapted BigQuery to monitor, analyze, and act on application performance data across all its stores and warehouses in real time—capabilities that were not as seamless in the on-premises environment.
With hundreds of projects on Google Cloud, The Home Depot’s cloud journey is well on track, but the company is always looking to the future. “As our customers’ needs have continued to evolve, and as technology has continued to evolve, our relationship with Google will continue to advance — to be able to innovate together, to be able to find new solutions together, to better serve our customers.”
Learn more about how The Home Depot is renovating its retail operation with SAP on Google Cloud.
More Relevant Stories for Your Company
How a Mid-Sized Firm is Shrinking Inventory Carryovers 50% with AI
For more than 10 years, NMK Textile Mills has manufactured bed linens for major retailers in the United States and Canada. As e-commerce exploded, the company’s co-founder saw an opportunity to grow the business. So, in addition to manufacturing bed linens wholesale for retail customers, NMK Textile Mills reworked its complete supply
The Future of Cloud Computing: Choose Your Own Services and Payment Options
As the saying goes, “it’s hard to make predictions, especially about the future.” Some organizations find it challenging to predict what cloud resources they’ll need in months or years ahead. Every organization is on its own unique cloud journey. To help, we’re developing new ways for customers to consume and
Beany’s Cloud-Based Accounting Solutions Transform Small Business Finance
Many people start a small business that aligns with their passions, but soon discover the day-to-day running of a business is very different than anticipated. Dealing with accounting, finance, and other daily activities can quickly overwhelm even the most promising of new businesses. Recognizing the unique challenges facing small businesses,
Google Cloud and Univision Partnership to Up the Ante in UX for Spanish-speaking Audience
The past year has given everyone lots to think about—about our priorities as people and as businesses. As the world retreated behind closed doors, we saw how shared interests and experiences can bring us together. As the world grappled with a common enemy, we witnessed just how differently individuals, communities
