8CIOReview | | DECEMBER 2022IN MY OPINIONTHE PANDEMIC ACCELERATED DIGITALBy Gavin Hupp, Vice President Information Technology, SeaWorld Parks & EntertainmentEvery company, in every industry has data, needs clean data, and needs to take action on data quickly and effectively. However, many organizations find themselves struggling with data, primarily because other initiatives that could quickly unlock new revenue streams tended to get prioritized above data infrastructure projects. Data science and analytics initiatives with the promise of unlocking insights, could also make sense being prioritized over pure data infrastructure initiatives. Implementing a new data strategy with revamped end-to-end data and analytics architecture is no easy feat, no matter how you tackle it (preferably incrementally and iteratively vs Big Bang Approach). Enter the Modern Data StackThe `Modern Data Stack' became more prominent over the last few years, with a proliferation of cloud technologies and vendors fueled by high demand and VC funds. While there is nothing necessarily new about what the modern data stack is set out to accomplish (empower your organization with the effective use of data), the ease of use, speed and potential capabilities are new. Some of the more popular vendors in the modern data stack include-· Fivetran and Stitch for data ingestion & ETL· Snowflake, Big Query, and Redshift for Warehousing· PowerBi, Tableau, and Looker for analytics & BI· Airflow for orchestration· DBT for transformation and · Soda for observability, to name a few. Databricks, Snowflake, Alteryx, and others fit into more than one category. Fundamental Data Management StackIn light of the new vendors, tools, and approaches to data delivery, operations, and management, it is important not to forget the fundamentals. The fundamentals as technologists and as data professionals. Here are just a few frameworks, processes, and books that cover the foundations that help me from time to time and are worth revisiting.RM Business Relationship ManagementEvery technologist does some form of business relationship management. They work with stakeholders to understand their problems and then deliver solutions. Data professionals are no different. They work with stakeholders to provide the right platforms and data and provide insights to stakeholders based on that data. Since stakeholders, developers, and analysts are all people, strong relationships need to be cultivated. Without establishing meaningful relationships, you will struggle with finding the root problems that need to be solved. The more meaningful problems you can solve for your stakeholders, the more value you can add. The more effectively you can communicate, set, and meet expectations, the better your relationships will be, the more successful you will be in your role, and the more successful your initiatives will be.The BRM Institute's House of BRM framework is an incredibly helpful guide to what it takes to build strong relationships within your organization, to become a trusted technology partner, and advance your organization. The closer technology and business strategy converge, the better. TOGAF (The Open Group Architecture Framework) Data truly is an enterprise asset and should be managed as holistically as possible across the enterprise. Your data architecture's capabilities and its costs need to tie back to enterprise goals and objectives. TOGAF is an enterprise architecture framework with roots in the late 1980s and has evolved into an extensive approach to enterprise architecture. While TOGAF can feel `heavy', and many feel it is outdated, its pillars and key concepts are essential.No matter the technology or resources deployed- it is critical to align with and be appropriate for the target state business architecture (i.e., the organizational structure, goals, objectives, business functions, services, processes, roles, and capabilities).TOGAF's Architectural Development Method (ADM) is an iterative and cyclical approach that includes setting the vision, defining the current state for each domain (starting with business and then information systems, which includes data architecture), the Gavin Hupp
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