Our framework addresses two key issues: It helps companies clarify the primary purpose of their data, and it guides them in strategic data management. Big data is what drives most modern businesses, and big data never sleeps. Data arrives from both “live” and “dead” data channels, and it is not easy to collect, organize, standardize, and manage this avalanche of data flow. At the same time, the Business Strategy needs to work from the premise that data is an important tool for reaching desired outcomes. Data security, privacy, and operational best practices are realized through the underlying Data Architecture, which, in a way, initiates the Data Governance process. This is explained in a HRB post titled What’s Your Data Strategy? We had databases, we had some ETL, and then we’d shoot out a report and that would be cool.” Because of the scale and number of options for working with data, along with a simultaneous level of granularity inherent in IoT, being a data architect is no longer synonymous with being a database developer or modeler building data flows for reporting purposes. The role of data in an organization is to cast light in all directions and fully illuminate a situation, to unveil truth. — Data Flow Diagram. • Bass, L.; John, B.; & Kates, J. Achieving Usability Through Software Architecture, Carnegie Mellon University. In such a scenario, it is only natural that Data Strategy or Data Architecture will play key roles in running a business efficiently. Developing a modern data strategy and architecture to unleash the power of your data without the risk Big ideas, bold moves, lasting impact Unlocking the value of your data begins with treating data as an asset, making it a strategic organizational priority to protect, govern, curate, invest in, and leverage it as a competitive capability. Unfortunately, like Governance, Quality and Strategy, there’s a lot of misconceptions about Data Architecture. Data Architecture supports Data Strategy. We may share your information about your use of our site with third parties in accordance with our, Concept and Object Modeling Notation (COMN). It is, in effect, a checklist for developing a roadmap toward the digital transformation journey that companies are actively pursuing as part of their modernization efforts. According to the Data Management Body of Knowledge, the data architect “provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture.” According to the Open Group Architecture Framework (TOGAF), a data architect is … Role. Data Management vs. Data Strategy: a Framework for Business Success reveals why a solid Data Strategy is needed for maximum business success. Data Strategy and Data Architecture: A Closer Look, According to Peter Drucker, information is “Data endowed with relevance and purpose.”. Data architecture refers to the models, policies, rules, or standards that govern what data is collected, how it is stored, organized, and used in an organization’s systems. Data What? Most businesses rely on data-driven IT systems for acquiring transactional, operational, performance, customer behavior, and all other types of data affecting daily business processes. Data Architecture: Is it the Beginning of Data Governance? This paper also distinguishes “data” that is managed outside of application processes, not merely as a byproduct of such processes. Develop the Target Data Architecture that enables the Business Architecture and the Architecture Vision, while addressing the Request for Architecture Work and stakeholder concerns 2. Figure 2. How do we use data to support all of these processes, measure them, and then improve them from a business perspective. Facilitate alignment of IT and business systems. “It’s really about asking, ‘How can we use data to drive better business?’”, Algmin said he’s a big advocate for understanding data value, which he defines as the differential in business outcomes across three dimensions: increasing revenue, decreasing cost, or managing risk. In order to be effective with Data Strategy, he said, a baseline set of measurements must be put in place to measure results. It’s not how well you do your thing. Data Strategy and Data Architecture are not the only important pieces in Data Leadership, but without understanding the roles that they play, a business won’t be able to leverage that truth to its advantage. Since a fundamental goal of the architecture is to have absolutely unquestionable data quality and reliability, semantic clarity is the first step; but disciplined stewardship of the data, the concepts, and the business rules is the only way to move forward, past that first step, to achieve a robust and effective architecture. A Data Strategy is not merely the top-level vision either, it can expand into critical data domains such as Business Intelligence and eventually represent a family of strategies.”. “Beyond talent, data is probably the most important ingredient for delivering an AI solution.”, Photo Credit: Dmitriy Rybin/Shutterstock.com, © 2011 – 2020 DATAVERSITY Education, LLC | All Rights Reserved. Systems are then implemented to support real-time (or near real-time) data feeds, and complex, dynamic data relationships and hierarchies are rationalized. This virtual two-day program included 12 thought-provoking live online sessions on popular topics like building a Data Strategy, Data-Centric Architectures, Agile Data Governance, Data Modeling, AI Analytics, Blockchain for the data professional, and much more. Data Strategy! Answering these questions will help create your blueprint for the architecture,” he said, with high-level scaffolding for the overall concepts and building blocks for the details underneath. Data Architecture defines how data is acquired, stored, processed, distributed, and consumed. “A lot of enterprise architects, in my opinion, [became] too fond of the idea that they mattered by themselves. Global Data Strategy can assist you in building a data architecture foundation through: Identifying business requirements, rules & definitions via a business-centric data model Data Management is not just a collection of IT platforms, technologies, and tools. Add to Favorites. Translate business needs into data and system requirements. It covers how each function fits into the overall data management framework. Without Data Architecture, Advanced IT Technologies Cannot be Used. “Your whole point is to create business outcomes, and you don’t do that by doing Data Strategy. “Logically you cannot be as capable if you don’t have a full view into what’s around you,” he said. It’s how your thing helps your business be successful.”. The objectives of the Data Architecture part of Phase C are to: 1. With an agreed-on and built-in master data management (MDM) strategy, your enterprise is able to have a single version of the truth that synchronizes data to applications accessing that data. What data are we going to measure and then what do we need to do to that data to impact other business systems to achieve these data-driven business outcomes? The role of the data architect is changing significantly, he said. For competitive market intelligence, businesses need immediate access to actionable insights facilitated through advanced IT systems. People in the IT department have a functional skillset that benefits the greater whole, but they need to be considered part of the business, he said. It is not possible for any organization to realize the fruits of advanced IT technologies without a Data Architecture in place first. Incomplete. Data Architecture Enables Better Governance in Overall Data Strategy. However, it’s no longer the centerpiece of an enterprise’s data architecture strategy. The data may be processed in batch or in real time. gives a clear view of the widespread impact of Data Strategy in a business. “It’s really a subset—not an independently developed data-focused thing.”, Data Strategy, at its core, should work toward maximizing business impacts by aligning with Business Strategy. Data Architecture needs to look at finding and putting the right mechanisms in place to support business outcomes, which could be everything from data systems and data warehouses to visualization tools. “It’s really the best proxy for truth we have,” he said. Data architecture is the overarching strategy a company uses to govern the collection, storage and use of all the data important to a business. View data as a shared asset. Data Architecture defines how data is acquired, stored, processed, distributed, and consumed. The 2020 Action Plan is designed to be cross-cutting and to support agencies in fulfilling a wide array of legislative and administrative requirements, while also prioritizing foundational activities for agencies in developing a mature data asset management environment. How do we leverage the data that we have today? Data Strategy provides the basic blueprint for data storage architectures and its internal components. These tools lower development and operating costs by enabling the use of the (lower-cost) data lake and … Algmin said that Data Leadership is largely made of Data Architecture, but it’s also about becoming part of the business as well as providing support for behavior change; “Things that go above and beyond what Data Architecture is.”. As part of its data strategy an organization will require two ‘architectures’; one devoted to raw data, the other devoted to the information that can be garnered from that data.An organization’s data architecture will define how data is to be collected, stored, organized, distributed and consumed. Rules must be created to govern the structures of databases and file systems, as well as the processes which connect the data with the areas of the organization that require it. Federal Data Strategy Leveraging Data as a Strategic Asset . But really, whether you’re talking Data Architecture or Enterprise Architecture, until you’re creating business impact, you don’t matter at all.”. The Data Strategy not only sets the blueprint for managing data, but also measures how the data is directly responsible for the ROIs. The 3V’s i.e. “Data Strategy” is the essential component for success with data, regardless of architecture. Cookies SettingsTerms of Service Privacy Policy, We use technologies such as cookies to understand how you use our site and to provide a better user experience. They should also evolve over time, yet by identifying something as a “best practice,” it is less likely to be challenged over time, even when it ceases to be a best practice. Each business person has a unique view of the role of Data Architecture, and a few use the terms “Data Architecture” and Data Governance” interchangeably. Data Architects are specialists within the larger field of IT Architecture, while some have wider architecture experience – others do nothing but work with data and data systems. The organizational Data Strategy lays out the foundation for “identifying, accessing, sharing, understanding, and using” data. According to Data Governance vs. Data Architecture, the problem of visualizing Data Architecture is quite to similar to that in The Elephant and the Six Blind Men. Within that overall Data Leadership Framework, sit Data Strategy and Data Architecture as individual disciplines. Thus, data performs some defensive actions when it shields itself from breaches and corruption, and some offensive actions when it delivers actionable insights or increased revenue. The SAS Institute whitepaper The 5 Essential Components of a Data Strategy offers a clearer understanding of Data Strategy. Compare Data Storage Options ~10 mins. The overall goal of an organization’s Data Strategy and its subordinate activities are mitigating risks, improving Data Quality, streamlining business processes while reducing operating cost, developing and executing advanced Analytics for business gain, generating ROI from data-centric initiatives, leveraging and monetizing data assets, complying with regulatory policies, preventing data breaches or cyberattacks, and enabling new products or services. November 6, 2018. “Data only has value when you put it to use, and if you put it to use inappropriately, you can create a huge mess,” such as a privacy breach. Why Organizations Need a Data Strategy offers the perspective of a seasoned industry leader, Stephen Lahanas, the Vice President & IT Architect of Semantech Inc. With years of experience behind him, Lahanas states that: “A Data Strategy is not a list of generic principles or obvious statements (such as ‘Data is an Enterprise Asset’). Choose the Right Big Data Solution Also key is an ability to understand business-side challenges, a desire – and an ability – to interact with other business leaders, as well as a willingness to let go of the mentality that IT people are somehow different from other people in the business. We start by inspecting current systems and workflows to define and articulate a data architecture and integration strategy.