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nRhiJb-DbgRPb-wNfPc-cGMI2b"><div class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c nRhiJb-BFbNVe-r8s4j-bMElCd dIsJJe" track-name="data analytics"track-type="tag">Data Analytics</div><div class="nRhiJb-ObfsIf"><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-R6PoUb"></div><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-EehZO nRhiJb-fmcmS-oXtfBe"><h1 class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-ibL1re"><div class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-ibL1re"><span class="FewWi"></span>How Deutsche Bank built a new retail data platform on Google Cloud</div></h1></div></div><div class="nRhiJb-fmcmS-oXtfBe dEogG">November 13, 2024</div></div></section><div class="EKklye"><div class="nRhiJb-DARUcf ZWw7T"><div class="npzWPc"><div class="dzoHJ"><div class="nRhiJb-DX2B6 nRhiJb-DX2B6-OWXEXe-h30Snd"><div class="nRhiJb-j5y3u"><ul class="nRhiJb-Qijihe phRaUe" role="list"><li class="hpHPGf"><a class="nRhiJb-ARYxNe" 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Deutsche Bank built a new retail data platform on Google Cloud%0A%0AA closer look at Deutsche Bank’s Private Bank data platform — its requirements, architecture, services, and management and operations.%0A%0Acloud.google.com/blog/products/data-analytics/inside-deutsche-banks-pbdp-retail-data-platform"track-metadata-module="social icons" target="_blank" rel="noopener"><svg class="nRhiJb-Bz112c nRhiJb-Bz112c-OWXEXe-DX2B6 nRhiJb-Bz112c-OWXEXe-nSuQf" viewBox="0 0 24 24" role="presentation" aria-hidden="true" role="presentation" aria-hidden="true"><path d="M20 4H4c-1.1 0-2 .9-2 2v12c0 1.1.9 2 2 2h16c1.1 0 2-.9 2-2V6c0-1.1-.9-2-2-2zm-.8 2L12 10.8 4.8 6h14.4zM4 18V7.87l8 5.33 8-5.33V18H4z"></path></svg></a></li></ul></div></div></div></div></div><div><section class="nRhiJb-DARUcf"><div class="nRhiJb-DbgRPb-wNfPc-ma6Yeb nRhiJb-DbgRPb-wNfPc-cGMI2b"><section class="DA9Qj nRhiJb-ObfsIf nRhiJb-fmcmS-oXtfBe"><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-ibL1re"></div><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-II5mzb kWSSdd"><h5 class="cHE8Ub Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c">Vladimir Elvov</h5><p class="nRhiJb-qJTHM khCp7b">Lead Customer Engineer, Data & Analytics</p></div><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-II5mzb kWSSdd"><h5 class="cHE8Ub Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c">Lars Fockele</h5><p class="nRhiJb-qJTHM khCp7b">Lead Data Engineer, Deutsche Bank AG</p></div></section></div></section><div class="nRhiJb-DARUcf"><div class="nRhiJb-ObfsIf nRhiJb-DbgRPb-wNfPc-ma6Yeb nRhiJb-DbgRPb-qWD73c-cGMI2b"><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-ibL1re dzoHJ"><div class="aLW4J" track-metadata-module="left rail"><h5 class="qZDXV Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-wNfPc">Google Cloud Summit Series</h5><p class="nRhiJb-cHYyed Mrfygc nRhiJb-BP2Omd-ma6Yeb-KE6vqe nRhiJb-DbgRPb-R6PoUb-cGMI2b">Discover the latest in AI, Security, Workspace, App Dev, & more.</p><a class="nRhiJb-LgbsSe nRhiJb-LgbsSe-OWXEXe-CNusmb-o6Shpd " href="https://cloudonair.withgoogle.com/summit_series_24?utm_source=cgc-blog&utm_medium=blog&utm_campaign=summit-series-2024&utm_content=summit-series-left-hand-rail-cta&utm_term=-" track-metadata-module="left rail"track-metadata-module_headline="google cloud summit series" track-name="register"track-type="button"track-metadata-position="cta"track-metadata-eventdetail="cloudonair.withgoogle.com/summit_series_24?utm_source=cgc-blog&utm_medium=blog&utm_campaign=summit-series-2024&utm_content=summit-series-left-hand-rail-cta&utm_term=-">Register </a></div></div><div class="OYL9D nRhiJb-kR0ZEf-OWXEXe-GV1x9e-OiUrBf" jsname="tx2NYc"><section class="Wy08Ac nRhiJb-qJTHM-OWXEXe-hJDwNd nRhiJb-DbgRPb-II5mzb-cGMI2b"><span class="dQQu7c" jsaction="rcuQ6b:npT2md" jscontroller="YSybTb" data-track-type="" soy-skip ssk='5:kbe95'><p style="text-align:justify"><span style="vertical-align:baseline">Getting insights into customer’s preferences and needs is crucial for any modern business — and that’s especially true for a retail bank. Insights from customer data help deliver improved customer experiences through custom tailored products, better services, and higher levels of automation. But to gain these customer insights, you need your input data to be in a common data platform. At the same time, data volumes continue to grow and there are always new real-time input sources cropping up. To address these needs, whatever solution you pick has to be scalable. </span></p> <p style="text-align:justify"><span style="vertical-align:baseline">With the data of over 20 million private, commercial and corporate partners and customers</span><span style="vertical-align:baseline"> Deutsche Bank decided to build such a data platform on Google Cloud that it calls the Private Bank data platform (PBDP). It's a transformative addition to Deutsche Bank’s IT capabilities:</span></p> <p style="padding-left:40px"><span style="font-style:italic;vertical-align:baseline">“In collaboration with Google we established one central and holistic data platform for Deutsche Bank with flexible data modeling options, an analytical workplace for exploration, prototyping and analysis and easy data ingestion into Google Cloud using real-time events and daily batch processes. Our new Data Platform serves as a cornerstone of our Bank’s strategic approach to consolidate data using a modern, cloud-based tech stack and is a fundamental enabler of multiple initiatives in the Bank. Having one place where you can find all your relevant data for your data consumer needs will enable multiple different future Data Driven operational and analytical use cases.”</span><span style="vertical-align:baseline"> - Jan Struewing, Director, Domain Lead Private Bank Data Platform, Deutsche Bank</span></p> <p style="text-align:justify"><span style="vertical-align:baseline">To inspire organizations that are also building a data platform on Google Cloud, in this blog, we take a deeper look at Deutsche Bank’s PBDP – its requirements, its architecture, the services that it runs, and Deutsche Bank’s approach to management and operations. </span></p></span></section><section class="k6ctOd"><aside class="IwVNTb"><div class="ecJG2e nRhiJb-ObfsIf"><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-OiUrBf nRhiJb-snVHke-ibL1re-X66g3b nRhiJb-snVHke-R6PoUb-UFsB2c"><h4 class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c">$300 in free credit to try Google Cloud data analytics</h4><p class="nRhiJb-qJTHM nRhiJb-DbgRPb-R6PoUb-ma6Yeb"><span class="dQQu7c" jsaction="rcuQ6b:npT2md" jscontroller="YSybTb" data-track-type="" soy-skip ssk='5:kbe95'><p>Bulid intelligent apps using real-time data insights with $300 in free credit for new customers. Plus, all customers get free monthly usage of 20+ products, including BigQuery.</p></span></p><a class="nRhiJb-LgbsSe nRhiJb-LgbsSe-OWXEXe-MNynB-o6Shpd LZTd1c" href="http://console.cloud.google.com/freetrial?redirectPath=/bigquery/" target="_blank" rel="noopener" track-name="start building for free"track-type="button"track-metadata-position="body"track-metadata-eventdetail="http://console.cloud.google.com/freetrial?redirectPath=/bigquery/"track-metadata-module="aside"track-metadata-module_headline="$300 in free credit to try google cloud data analytics" track-name="start building for free"track-type="button"track-metadata-position="body"track-metadata-eventdetail="http://console.cloud.google.com/freetrial?redirectPath=/bigquery/">Start building for free </a></div></div></aside></section><section class="Wy08Ac nRhiJb-qJTHM-OWXEXe-hJDwNd nRhiJb-DbgRPb-II5mzb-cGMI2b"><span class="dQQu7c" jsaction="rcuQ6b:npT2md" jscontroller="YSybTb" data-track-type="" soy-skip ssk='5:kbe95'><h3 style="text-align:justify"><strong style="vertical-align:baseline">The capabilities of a modern data platform</strong></h3> <p style="text-align:justify"><span style="vertical-align:baseline">The foundation of the Deutsche Bank’s PBDP is a layer that provisions data centrally and continuously in a well-governed and easy to consume way. This part of the PBDP is also referred to as the Data Core. Data arrives from various systems at different speeds, which means that the PBDP needs to be able to pick up both files and events from the data producers. It does this through batch and real-time ingestion mechanisms that eventually land the data in BigQuery — or in the case of event data, in Pub/Sub for real-time consumption. </span><span style="vertical-align:baseline">Data access is governed based on the rights and permissions of consumers and the review of the CDO Residency and Access team to ensure that data access is compliant to the respective regulations and policies.</span><span style="vertical-align:baseline"> Above all, the PBDP also provides metadata on top of the input data to make data discovery and access simple for consumers. </span></p> <p style="text-align:justify"><span style="vertical-align:baseline">The Data Core is the cornerstone of the PBDP because it allows for simple, central data retrieval. This means that data consumers don’t have to source the same data multiple times through parallel pipelines, but can instead leverage a central data store. This improves data quality and reliability, and makes data sharing much more cost efficient than a point-to-point solution between producers and consumers. It also makes getting access to data a much faster process from an organizational point of view due to centralized and standardized processes for onboarding consumers rather than custom processes and point-to-point integrations. </span></p> <p style="text-align:justify"><span style="vertical-align:baseline">PBDP data can be consumed in two ways from BigQuery: Either in the “raw” format as it comes directly from the source systems, or through a data model. This data model is based on </span><a href="https://services.google.com/fh/files/misc/google-cloud-data-vault_b.pdf" rel="noopener" target="_blank"><span style="text-decoration:underline;vertical-align:baseline">the Data Vault 2.0 paradigm</span></a><span style="vertical-align:baseline">, where the data in the business vault layer follows the same data model, which is agnostic to the source systems' data models.</span></p> <p style="text-align:justify"><span style="vertical-align:baseline">There are two types of consumers — data-driven products or an analytical workplace on top of the PBDP:</span></p> <ul> <li style="list-style-type:disc;vertical-align:baseline"> <p style="text-align:justify"><span style="vertical-align:baseline">A data-driven product is basically an application that contains business logic specific to the insights it is supposed to offer to its users based on the data it is processing. It is owned by a team in the bank and sources its input data from the PBDP’s Data Core, while taking care of its specific data transformations on its own. Input data can be retrieved either from BigQuery, or from Pub/Sub directly for real-time data processing. To implement these transformations, data-driven products can utilize PBDP out-of-the-box tooling and templates.</span></p> </li> <li style="list-style-type:disc;vertical-align:baseline"> <p style="text-align:justify"><span style="vertical-align:baseline">The analytical workplace allows exploration and analysis of the data on the PBDP Data Core in an interactive manner so that new insights can be derived and new algorithms can be developed. It is commonly used by data scientists and analysts who leverage standardized solutions from the PBDP, for example Vertex AI notebooks. The artifacts that are the results of the work on the analytical workplace can eventually be productionized in the form of a new data driven product. </span></p> </li> </ul> <h3 style="text-align:justify"><strong style="vertical-align:baseline">PBDP architectural overview </strong></h3> <p style="text-align:justify"><span style="vertical-align:baseline">The following diagram shows the high-level architecture of Deutsche Bank’s PBDP. It focuses on the interfaces between the on-premises estate, located inside the Deutsche Bank network, and the PBDP running inside Google Cloud. With this architecture, Deutsche Bank was able to initial-load billions of records during the Postbank-Deutsche Bank migration and process millions of records per day for its consumers.</span></p></span></section><section class="QzPuud"><div><section><figure class="NEBdNd"><section class="PBkdHd DhGbH" jscontroller="SCGBie" jsaction="rcuQ6b:npT2md"><img class="JcsBte mZzdH ZOnyjc" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png" alt="https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png" jsname='P3Vluc' jsaction="click:HTIlC" loading="lazy"/><section class="glue-modal glue-modal--dark QHdDac" role="dialog" aria-modal="true"><img class="JcsBte mZzdH ZOnyjc" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png" alt="https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png" jsname='P3Vluc' jsaction="click:HTIlC" loading="lazy"/><button class="glue-modal__close-btn" tabindex="0" aria-label="Close this modal"></button></section></section></figure></section></div></section><section class="Wy08Ac nRhiJb-qJTHM-OWXEXe-hJDwNd nRhiJb-DbgRPb-II5mzb-cGMI2b"><span class="dQQu7c" jsaction="rcuQ6b:npT2md" jscontroller="YSybTb" data-track-type="" soy-skip ssk='5:kbe95'><h3 style="text-align:justify"><strong style="vertical-align:baseline">A central data hub for a private bank</strong></h3> <p style="text-align:justify"><span style="vertical-align:baseline">PBDP’s input data sources are pretty broad, and include the main information needed for data-driven products like the new online banking platform, which was built using cloud-native services on Google Cloud. The data for the online banking platform covers core customer information, current accounts data (a.k.a. checking accounts), credit card data, savings accounts data, partner data, loans data and data about securities/brokerage accounts. It is sourced from SAP, mainframes, relational databases and other systems of record. </span></p> <p style="text-align:justify"><span style="vertical-align:baseline">In addition to serving as a central data platform for the private bank, PBDP functions as a key integration layer between the bank’s on-prem systems for core banking and its new online banking platform. That’s important because when migrating from an on-prem estate to the cloud, not all applications can move at once. Having an integration layer or middleware capability between the on-prem and cloud-based systems is tremendously important. It “de-risks” the migration by enabling a phased approach and integrates the on-prem and cloud-based systems in a scalable way.</span></p> <p style="text-align:justify"><span style="vertical-align:baseline">In addition to the online banking platform, other PBDP consumers include accounts reporting, the client sales warehouse, financial reporting, analytical tooling for commercial clients in Germany and others, with new consumers being constantly onboarded.</span></p> <h3 style="text-align:justify"><strong style="vertical-align:baseline">Key roadmap activities</strong></h3> <p style="text-align:justify"><span style="vertical-align:baseline">There are some areas of improvement for the PB Data Platform, like for example the introduction of a staging area/level which will give the possibility to add further housekeeping or data management tasks. Another example is adding row-level security tags to the data rows, before the data will be written into the final tables and provided to consumers. In addition, the team is working on detailed implementation patterns linked to the Enterprise Architecture Data Principles and Data Standards, as well as extending the use of Enterprise Data Capabilities and being aligned to DB’s group-wide data strategy. This includes further alignment on working packages like: </span></p> <ul> <li style="list-style-type:disc;vertical-align:baseline"> <p style="text-align:justify"><span style="vertical-align:baseline">Usage of a single group-wide data registry</span></p> </li> <li style="list-style-type:disc;vertical-align:baseline"> <p style="text-align:justify"><span style="vertical-align:baseline">Aligned data standards for data interfaces (pathways), common data modeling techniques, and data harmonization </span></p> </li> <li style="list-style-type:disc;vertical-align:baseline"> <p style="text-align:justify"><span style="vertical-align:baseline">Enhancing the alignment to the concepts of Data Products and Data Mesh to further streamline data consumption </span></p> </li> </ul> <h3 style="text-align:justify"><strong style="vertical-align:baseline">Embracing a DevOps way of working </strong></h3> <p style="text-align:justify"><span style="vertical-align:baseline">A modern data platform requires a modern approach to development and operations. In addition to adopting DevOps principles for their data platform, the development team has also embraced automation to streamline infrastructure provisioning and CI/CD processes.</span></p> <p style="text-align:justify"><span style="vertical-align:baseline">The team manages their Google Cloud infrastructure through all its different environments (from development, to testing, to production) with Terraform, which allows them to define their infrastructure in code, ensuring consistency and reducing the risk of manual errors. Developers, meanwhile, have automated the provisioning and management of data platform infrastructure including virtual machines, network configurations, storage resources, security configurations and many more.</span></p> <p style="text-align:justify"><span style="vertical-align:baseline">The team stores its Terraform scripts in GitHub so they can version control their infrastructure and easily track changes. This enables them to roll back changes if necessary and maintain a consistent state across different environments. At the same time, a series of GitHub Actions workflows perform the typical CI/CD steps. Automating infrastructure provisioning and CI/CD processes brings numerous benefits to the team, including reduced manual effort, improved consistency, faster delivery and enhanced reliability.</span><span style="vertical-align:baseline"> </span></p> <p style="text-align:justify"><span style="vertical-align:baseline">Finally, Deutsche Bank monitors all important operations on the data platform with native Google Cloud monitoring services. Every malfunction of the system triggers alerts that are automatically sent to a support mailbox and a dedicated team chat. With all of this, developers are able to build, deploy and operate the complete PBDP as a single DevOps team.</span></p> <p><span style="vertical-align:baseline">These capabilities and architectural patterns allow Deutsche Bank’s PBDP to scale further and onboard more analytical use cases seamlessly - something many organizations could benefit from. If you want to learn more about how to get started, </span><a href="https://cloud.google.com/contact"><span style="text-decoration:underline;vertical-align:baseline">reach out to the Google Cloud team</span></a><span style="vertical-align:baseline">.</span></p></span></section><section class="kcBhad"><section class="Fabbec"><span class="WrMNjb">Posted in</span><ul class="FzXI4e"><li class="I4B51b"><a href="https://cloud.google.com/blog/products/data-analytics" track-metadata-position="body"track-metadata-eventdetail="cloud.google.com/blog/products/data-analytics"track-metadata-module="tag list"track-metadata-module_headline="posted in">Data Analytics</a></li><li class="I4B51b"><a href="https://cloud.google.com/blog/topics/customers" track-metadata-position="body"track-metadata-eventdetail="cloud.google.com/blog/topics/customers"track-metadata-module="tag list"track-metadata-module_headline="posted in">Customers</a></li><li class="I4B51b"><a 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track-name="data analytics"track-type="tag">Data Analytics</div><h3 class="Qwf2Db-MnozTc HGFKtc Qwf2Db-MnozTc-OWXEXe-MnozTc-wNfPc">Secure your data ecosystem: a multi-layered approach with Google Cloud</h3><p class="nRhiJb-cHYyed dTIXyb nRhiJb-DbgRPb-R6PoUb-ma6Yeb">By Nic Smith • 3-minute read</p></div></div></a></div></div><div class=" QaGyvd nRhiJb-kR0ZEf-OWXEXe-GV1x9e-c5RTEf nRhiJb-kR0ZEf-OWXEXe-GV1x9e-qWD73c-V2iZpe"><div class="mA0uBe"><a href="https://cloud.google.com/blog/products/data-analytics/puma-bigquery-customer-engagement" class="lD2oe" track-name="how puma leverages built-in intelligence with bigquery for greater customer engagement"track-type="card"track-metadata-eventdetail="cloud.google.com/blog/products/data-analytics/puma-bigquery-customer-engagement"><div class="AhkbS "><div class="hqnDEf"><section class="PBkdHd "><img class=" D5RK8d" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/puma-website-store-suede-xl_1.max-700x700.jpg" 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management and operations.",[1731459600],"https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-2600x2600.jpg","https://cloud.google.com/blog/products/data-analytics/inside-deutsche-banks-pbdp-retail-data-platform",[1731459603,772454000]],[["Vladimir Elvov","Lead Customer Engineer, Data \u0026 Analytics"],["Lars Fockele","Lead Data Engineer, Deutsche Bank AG"]],[null,"\u003cscript type\u003d\"application/ld+json\"\u003e{\"@context\":\"https://schema.org\",\"@type\":\"BlogPosting\",\"@id\":\"https://cloud.google.com/blog/products/data-analytics/inside-deutsche-banks-pbdp-retail-data-platform\",\"headline\":\"Inside Deutsche Bank\u2019s PBDP retail data platform\",\"description\":\"A closer look at Deutsche Bank\u2019s Private Bank data platform \u2014 its requirements, architecture, services, and management and operations.\",\"image\":\"https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-2600x2600.jpg\",\"author\":[{\"@type\":\"Person\",\"name\":\"Vladimir Elvov\",\"url\":\"\"},{\"@type\":\"Person\",\"name\":\"Lars Fockele\",\"url\":\"\"}],\"datePublished\":\"2024-11-13\",\"publisher\":{\"@type\":\"Organization\",\"name\":\"Google Cloud\",\"logo\":{\"@type\":\"ImageObject\",\"url\":\"https://www.gstatic.com/devrel-devsite/prod/v8bb8fa0afe9a8c3a776ebeb25d421bb443344d789b3607754dfabea418b8c4be/cloud/images/cloud-logo.svg\"}},\"url\":\"https://cloud.google.com/blog/products/data-analytics/inside-deutsche-banks-pbdp-retail-data-platform\",\"keywords\":[\"Data Analytics\",\"Customers\",\"Financial Services\"],\"timeRequired\":\"PT7M\"}\u003c/script\u003e"],["How Deutsche Bank built a new retail data platform on Google Cloud"],null,null,[[null,null,[null,[null,"\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eGetting insights into customer\u2019s preferences and needs is crucial for any modern business \u2014 and that\u2019s especially true for a retail bank. Insights from customer data help deliver improved customer experiences through custom tailored products, better services, and higher levels of automation. But to gain these customer insights, you need your input data to be in a common data platform. At the same time, data volumes continue to grow and there are always new real-time input sources cropping up. To address these needs, whatever solution you pick has to be scalable.\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eWith the data of over 20 million private, commercial and corporate partners and customers\u003c/span\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003e Deutsche Bank decided to build such a data platform on Google Cloud that it calls the Private Bank data platform (PBDP). It's a transformative addition to Deutsche Bank\u2019s IT capabilities:\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"padding-left:40px\"\u003e\u003cspan style\u003d\"font-style:italic;vertical-align:baseline\"\u003e\u201cIn collaboration with Google we established one central and holistic data platform for Deutsche Bank with flexible data modeling options, an analytical workplace for exploration, prototyping and analysis and easy data ingestion into Google Cloud using real-time events and daily batch processes. Our new Data Platform serves as a cornerstone of our Bank\u2019s strategic approach to consolidate data using a modern, cloud-based tech stack and is a fundamental enabler of multiple initiatives in the Bank. Having one place where you can find all your relevant data for your data consumer needs will enable multiple different future Data Driven operational and analytical use cases.\u201d\u003c/span\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003e - Jan Struewing, Director, Domain Lead Private Bank Data Platform, Deutsche Bank\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eTo inspire organizations that are also building a data platform on Google Cloud, in this blog, we take a deeper look at Deutsche Bank\u2019s PBDP \u2013 its requirements, its architecture, the services that it runs, and Deutsche Bank\u2019s approach to management and operations. \u003c/span\u003e\u003c/p\u003e"]]],[null,["$300 in free credit to try Google Cloud data analytics",null,"Start building for free","http://console.cloud.google.com/freetrial?redirectPath\u003d/bigquery/",[null,"\u003cp\u003eBulid intelligent apps using real-time data insights with $300 in free credit for new customers. Plus, all customers get free monthly usage of 20+ products, including BigQuery.\u003c/p\u003e"]]],[null,null,[null,[null,"\u003ch3 style\u003d\"text-align:justify\"\u003e\u003cstrong style\u003d\"vertical-align:baseline\"\u003eThe capabilities of a modern data platform\u003c/strong\u003e\u003c/h3\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThe foundation of the Deutsche Bank\u2019s PBDP is a layer that provisions data centrally and continuously in a well-governed and easy to consume way. This part of the PBDP is also referred to as the Data Core. Data arrives from various systems at different speeds, which means that the PBDP needs to be able to pick up both files and events from the data producers. It does this through batch and real-time ingestion mechanisms that eventually land the data in BigQuery \u2014 or in the case of event data, in Pub/Sub for real-time consumption. \u003c/span\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eData access is governed based on the rights and permissions of consumers and the review of the CDO Residency and Access team to ensure that data access is compliant to the respective regulations and policies.\u003c/span\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003e Above all, the PBDP also provides metadata on top of the input data to make data discovery and access simple for consumers.\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThe Data Core is the cornerstone of the PBDP because it allows for simple, central data retrieval. This means that data consumers don\u2019t have to source the same data multiple times through parallel pipelines, but can instead leverage a central data store. This improves data quality and reliability, and makes data sharing much more cost efficient than a point-to-point solution between producers and consumers. It also makes getting access to data a much faster process from an organizational point of view due to centralized and standardized processes for onboarding consumers rather than custom processes and point-to-point integrations.\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003ePBDP data can be consumed in two ways from BigQuery: Either in the \u201craw\u201d format as it comes directly from the source systems, or through a data model. This data model is based on \u003c/span\u003e\u003ca href\u003d\"https://services.google.com/fh/files/misc/google-cloud-data-vault_b.pdf\" rel\u003d\"noopener\" target\u003d\"_blank\"\u003e\u003cspan style\u003d\"text-decoration:underline;vertical-align:baseline\"\u003ethe Data Vault 2.0 paradigm\u003c/span\u003e\u003c/a\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003e, where the data in the business vault layer follows the same data model, which is agnostic to the source systems' data models.\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThere are two types of consumers \u2014 data-driven products or an analytical workplace on top of the PBDP:\u003c/span\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli style\u003d\"list-style-type:disc;vertical-align:baseline\"\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eA data-driven product is basically an application that contains business logic specific to the insights it is supposed to offer to its users based on the data it is processing. It is owned by a team in the bank and sources its input data from the PBDP\u2019s Data Core, while taking care of its specific data transformations on its own. Input data can be retrieved either from BigQuery, or from Pub/Sub directly for real-time data processing. To implement these transformations, data-driven products can utilize PBDP out-of-the-box tooling and templates.\u003c/span\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli style\u003d\"list-style-type:disc;vertical-align:baseline\"\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThe analytical workplace allows exploration and analysis of the data on the PBDP Data Core in an interactive manner so that new insights can be derived and new algorithms can be developed. It is commonly used by data scientists and analysts who leverage standardized solutions from the PBDP, for example Vertex AI notebooks. The artifacts that are the results of the work on the analytical workplace can eventually be productionized in the form of a new data driven product.\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3 style\u003d\"text-align:justify\"\u003e\u003cstrong style\u003d\"vertical-align:baseline\"\u003ePBDP architectural overview\u00a0\u003c/strong\u003e\u003c/h3\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThe following diagram shows the high-level architecture of Deutsche Bank\u2019s PBDP. It focuses on the interfaces between the on-premises estate, located inside the Deutsche Bank network, and the PBDP running inside Google Cloud. With this architecture, Deutsche Bank was able to initial-load billions of records during the Postbank-Deutsche Bank migration and process millions of records per day for its consumers.\u003c/span\u003e\u003c/p\u003e"]]],[null,null,null,null,null,null,null,null,[[[null,""],["https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png","https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-1100x1100.png 1060w, https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png 1994w"," 1060px, 1994px","https://storage.googleapis.com/gweb-cloudblog-publish/images/1_l2TejA4.max-2000x2000.png"],null,3]]],[null,null,[null,[null,"\u003ch3 style\u003d\"text-align:justify\"\u003e\u003cstrong style\u003d\"vertical-align:baseline\"\u003eA central data hub for a private bank\u003c/strong\u003e\u003c/h3\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003ePBDP\u2019s input data sources are pretty broad, and include the main information needed for data-driven products like the new online banking platform, which was built using cloud-native services on Google Cloud. The data for the online banking platform covers core customer information, current accounts data (a.k.a. checking accounts), credit card data, savings accounts data, partner data, loans data and data about securities/brokerage accounts. It is sourced from SAP, mainframes, relational databases and other systems of record.\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eIn addition to serving as a central data platform for the private bank, PBDP functions as a key integration layer between the bank\u2019s on-prem systems for core banking and its new online banking platform. That\u2019s important because when migrating from an on-prem estate to the cloud, not all applications can move at once. Having an integration layer or middleware capability between the on-prem and cloud-based systems is tremendously important. It \u201cde-risks\u201d the migration by enabling a phased approach and integrates the on-prem and cloud-based systems in a scalable way.\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eIn addition to the online banking platform, other PBDP consumers include accounts reporting, the client sales warehouse, financial reporting, analytical tooling for commercial clients in Germany and others, with new consumers being constantly onboarded.\u003c/span\u003e\u003c/p\u003e\n\u003ch3 style\u003d\"text-align:justify\"\u003e\u003cstrong style\u003d\"vertical-align:baseline\"\u003eKey roadmap activities\u003c/strong\u003e\u003c/h3\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThere are some areas of improvement for the PB Data Platform, like for example the introduction of a staging area/level which will give the possibility to add further housekeeping or data management tasks. Another example is adding row-level security tags to the data rows, before the data will be written into the final tables and provided to consumers. In addition, the team is working on detailed implementation patterns linked to the Enterprise Architecture Data Principles and Data Standards, as well as extending the use of Enterprise Data Capabilities and being aligned to DB\u2019s group-wide data strategy. This includes further alignment on working packages like:\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli style\u003d\"list-style-type:disc;vertical-align:baseline\"\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eUsage of a single group-wide data registry\u003c/span\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli style\u003d\"list-style-type:disc;vertical-align:baseline\"\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eAligned data standards for data interfaces (pathways), common data modeling techniques, and data harmonization\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003cli style\u003d\"list-style-type:disc;vertical-align:baseline\"\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eEnhancing the alignment to the concepts of Data Products and Data Mesh to further streamline data consumption\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3 style\u003d\"text-align:justify\"\u003e\u003cstrong style\u003d\"vertical-align:baseline\"\u003eEmbracing a DevOps way of working\u00a0\u003c/strong\u003e\u003c/h3\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eA modern data platform requires a modern approach to development and operations. In addition to adopting DevOps principles for their data platform, the development team has also embraced automation to streamline infrastructure provisioning and CI/CD processes.\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThe team manages their Google Cloud infrastructure through all its different environments (from development, to testing, to production) with Terraform, which allows them to define their infrastructure in code, ensuring consistency and reducing the risk of manual errors. Developers, meanwhile, have automated the provisioning and management of data platform infrastructure including virtual machines, network configurations, storage resources, security configurations and many more.\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThe team stores its Terraform scripts in GitHub so they can version control their infrastructure and easily track changes. This enables them to roll back changes if necessary and maintain a consistent state across different environments. At the same time, a series of GitHub Actions workflows perform the typical CI/CD steps. Automating infrastructure provisioning and CI/CD processes brings numerous benefits to the team, including reduced manual effort, improved consistency, faster delivery and enhanced reliability.\u003c/span\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003e\u00a0\u003c/span\u003e\u003c/p\u003e\n\u003cp style\u003d\"text-align:justify\"\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eFinally, Deutsche Bank monitors all important operations on the data platform with native Google Cloud monitoring services. Every malfunction of the system triggers alerts that are automatically sent to a support mailbox and a dedicated team chat. With all of this, developers are able to build, deploy and operate the complete PBDP as a single DevOps team.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003eThese capabilities and architectural patterns allow Deutsche Bank\u2019s PBDP to scale further and onboard more analytical use cases seamlessly - something many organizations could benefit from. If you want to learn more about how to get started, \u003c/span\u003e\u003ca href\u003d\"https://cloud.google.com/contact\"\u003e\u003cspan style\u003d\"text-decoration:underline;vertical-align:baseline\"\u003ereach out to the Google Cloud team\u003c/span\u003e\u003c/a\u003e\u003cspan style\u003d\"vertical-align:baseline\"\u003e.\u003c/span\u003e\u003c/p\u003e"]]]],[["Data Analytics","Dataproc Serverless: Now faster, easier and smarter","Running Dataproc Serverless now has Native query execution, integrated monitoring, and Gemini-powered proactive autotuning and troubleshooting.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg"],null,7,null,"https://cloud.google.com/blog/products/data-analytics/dataproc-serverless-performance-and-usability-updates",null,1,[["Pardha Saradhi Uppala","Product Manager"],["Virat Bansal","Software Engineer"]],null,"55584"],["Data Analytics","Secure your data ecosystem: a multi-layered approach with Google Cloud","A new ebook, Building a Secure Data Platform with Google Cloud, details the tools available to protect your data as you use it to grow your business.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg"],null,3,null,"https://cloud.google.com/blog/products/data-analytics/learn-how-to-build-a-secure-data-platform-with-google-cloud-ebook",null,1,[["Nic Smith","Head of Product Marketing, Data \u0026 Analytics"],["Robert Sadowski","Director, Product Marketing, Security \u0026 Trust"]],null,"55573"],["Data Analytics","How PUMA leverages built-in intelligence with BigQuery for greater customer engagement","To improve its customer engagement and prepare for a cookieless future via advanced audience segmentation, PUMA partnered with Google Cloud.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/puma-website-store-suede-xl_1.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/puma-website-store-suede-xl_1.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/puma-website-store-suede-xl_1.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/puma-website-store-suede-xl_1.max-700x700.jpg"],null,4,null,"https://cloud.google.com/blog/products/data-analytics/puma-bigquery-customer-engagement",null,1,[["Tsuki Schmidt","Teamhead Performance Marketing E-Commerce Europe, PUMA"],["Maxime Riche","Teamhead Analytics \u0026 Business Intelligence Global Retail \u0026 E-Commerce, PUMA"]],null,"55552"],["Data Analytics","Dataplex Automatic Discovery makes Cloud Storage data available for Analytics and governance","Dataplex can now automatically discover and catalog Google Cloud Storage data, extracting metadata, and creating BigQuery and BigLake tables.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/09_-_Data_Analytics_tFH57V6.max-400x400.jpg 324w, 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