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is America’s largest buy-here, pay-here dealership network. Founded in 1989, Byrider automotive sales and service franchises have sold more than 1.2 million cars at more than 150 locations across the country. With the vision to be the consumer choice in helping people get a fresh opportunity to finance and own a quality vehicle, Byrider offers a range of fully inspected vehicles, backed with warranties, service options, and flexible financing, credit, and payment options.",[],"normal","Byrider",false,"black",[268,276,283],{"_key":269,"_type":270,"description":271,"image":272,"title":275},"4cd26f2aaeda","tout","Byrider needed to modernize its data analytics platform to unify and democratize data access and insights across users for collaboration, innovation, and intelligent decision-making.",{"_type":69,"asset":273},{"_ref":274,"_type":73},"image-47b50bfd42d9d7c394d0be18ed64df669c053c07-96x96-svg","THE CHALLENGE  ",{"_key":277,"_type":270,"description":278,"image":279,"title":282},"2cfec0232ad5","Ollion identified Byrider’s need for business intelligence (BI) software that would streamline their analytics platform and drive unified data insights across internal teams and individual users. We implemented Looker, part of the Google Cloud Platform (GCP), as the primary tool to replace legacy spreadsheets with a single source of truth for advanced analytics and innovation.",{"_type":69,"asset":280},{"_ref":281,"_type":73},"image-bed83cb4561c08e3d5d85c4d3668125449bde8e6-96x96-svg","THE SOLUTION",{"_key":284,"_type":270,"description":285,"image":286,"title":289},"d800fc342898","After working with Ollion, Byrider can more efficiently and effectively impact their bottom line by harnessing their data for smarter decision-making. 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We created a new data model and designed ETL processes that enabled Byrider to take full advantage of the scale and speed of their Amazon Redshift data warehouse. While the data warehouse was a significant step forward, Byrider did not have the analytics and BI necessary to operationalize the data they sourced.",[],{"_key":330,"_type":255,"assets":227,"children":331,"markDefs":336,"style":263},"14bdf9631557",[332],{"_key":333,"_type":259,"marks":334,"text":335},"8d87472ce36d0",[],"Without a unified data platform, internal stakeholders either had to piecemeal their analytics based on a variety of sources and methodologies or burden database developers and DevOps teams to help track down useful insights. Certain reports were generated directly from the online transactional processing (OLTP) system, or client-side applications, rather than the warehouse. Due to the origin of these reports, their history and context were difficult to understand. 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Is this practice more or less successful than other practices?",[],{"_key":369,"_type":255,"children":370,"markDefs":375,"style":263},"0944e24fbd14",[371],{"_key":372,"_type":259,"marks":373,"text":374},"39677ef19f920",[],"These kinds of questions are asked every day in every firm, but the answers can depend on which data is used in the analysis and what metrics and measures define success. For our global law firm client, there was little consensus and way too much time debating contradictions in the data and interpreting and misinterpreting the answers.",[],{"_key":377,"_type":255,"children":378,"markDefs":383,"style":263},"6b9a2415c8c0",[379],{"_key":380,"_type":259,"marks":381,"text":382},"2df368541c5e0",[],"Their leadership wanted executives and lawyers to make proactive decisions firm-wide, but these users needed accurate data first and foremost. Our analysis showed that more than 80% of the users’ time was spent finding the data and creating the reports, with only 20% of the time spent on analyzing and taking action.",[],{"_key":385,"_type":255,"children":386,"markDefs":391,"style":320},"cad472a6d93c",[387],{"_key":388,"_type":259,"marks":389,"text":390},"5ddbc3158496",[],"The Impact  ",[],{"_key":393,"_type":255,"children":394,"markDefs":399,"style":263},"fc59ef11000c",[395],{"_key":396,"_type":259,"marks":397,"text":398},"4b48e3ff0764",[],"Ollion led a data and analytics strategy and planning process to map out our client’s vision, design the data architecture, select the right tools, and plan a long-term roadmap.",[],{"_key":401,"_type":255,"children":402,"level":407,"listItem":408,"markDefs":409,"style":263},"1cbebaf4070f",[403],{"_key":404,"_type":259,"marks":405,"text":406},"86ceb8bc34980",[],"The result was a comprehensive strategy that outlined not only the tools and technology needed but also the required organizational change initiatives to deliver near-term value while building to their long-term vision.",1,"bullet",[],{"_key":411,"_type":255,"children":412,"markDefs":417,"style":263},"171c799d8544",[413],{"_key":414,"_type":259,"marks":415,"text":416},"927bd7810a900",[],"With the goal of a “single source of the truth” in mind, our client’s CFO reached out to Ollion in the hopes of planning a centralized law firm data and reporting platform. He chose 2nd Watch because of our experience building out data strategies that balanced the needs of business users with a strong technical foundation. Our collaborative, strategy-first approach made our team the ideal partner to make this project a success.",[],{"_key":419,"_type":255,"children":420,"markDefs":425,"style":263},"b678a5caa4d9",[421],{"_key":422,"_type":259,"marks":423,"text":424},"8b19ebc211960",[],"Over the course of several months, our team worked closely with the client’s stakeholders to gain a comprehensive understanding of their goals, needs, pain points, and overall vision. Ollion conducted a series of discovery interviews with executives, functional managers, and partners. In these conversations, we explored the inefficiencies in data access and analysis and the potential value to the firm from a common view and shared understanding of problems and opportunities.",[],{"_key":427,"_type":255,"children":428,"markDefs":433,"style":263},"f82cde551af8",[429],{"_key":430,"_type":259,"marks":431,"text":432},"d263a4bd97650",[],"Then, we reviewed their existing infrastructure of databases, systems, and applications. We found numerous custom applications and siloed reporting efforts with their own distinct data sources. This separation kept our client from producing accurate, cohesive answers to questions asked by their practice group leaders and senior management team.",[],{"_key":435,"_type":255,"children":436,"markDefs":440,"style":263},"b9d14bbb299d",[437],{"_key":438,"_type":259,"marks":439,"text":250},"ac050596ca930",[],[],{"_key":442,"_type":255,"children":443,"markDefs":448,"style":320},"dce9134fa6ab",[444],{"_key":445,"_type":259,"marks":446,"text":447},"2bcae21634c1",[],"The Outcome ",[],{"_key":450,"_type":255,"children":451,"markDefs":456,"style":263},"1454046546f2",[452],{"_key":453,"_type":259,"marks":454,"text":455},"8d19180372d8",[],"The result for our client was a clear data and technical architecture that will support leading- edge analytical tools using consistent and accurate firm-wide data. A roadmap helped define the budget and schedule necessary to achieve their vision, and the organizational change recommendations define the people/process changes they need to make.",[],{"_key":458,"_type":255,"children":459,"markDefs":464,"style":263},"8e77ad8ccf5f",[460],{"_key":461,"_type":259,"marks":462,"text":463},"7274bdda49170",[],"By focusing on data strategy upfront, the client can implement their law firm data and reporting platform in a cost-effective, efficient way that will set them up for a competitive advantage using analytics insights.",[],"Diasbled",true,{"_type":69,"alt":468,"asset":469},"Legal Data Analytics Case Study",{"_ref":470,"_type":73},"image-1494a91561460d8064a70b553d348b73b459c437-1344x960-jpg","imageOnLeft",{"_key":473,"_type":349,"backgroundColor":350,"backgroundColorRevealed":250,"blockAccentColor":250,"blockBottomBorder":251,"blockSpacing":346,"body":474,"cmsLabel":513,"disabled":265,"image":514,"layout":471},"581856e413f034fa8fd3388e8115c696",[475,481,489,497,505],{"_key":385,"_type":255,"children":476,"markDefs":480,"style":320},[477],{"_key":388,"_type":259,"marks":478,"text":479},[],"The Solution",[],{"_key":482,"_type":255,"children":483,"markDefs":488,"style":263},"24aaaffb3a4a",[484],{"_key":485,"_type":259,"marks":486,"text":487},"4385445c3e660",[],"Ollion consultants from the Data Insights practice implemented Looker, a BI software and big data analytics platform, to address the challenges faced by Byrider. We focused on utilizing LookML, Looker’s data modeling language to create a semantic layer for capturing business logic, rather than defining it in data warehouse dimensional tables. This approach empowers business users with powerful analytics tools. Armed with these tools, Byrider’s data teams can explore different aspects of the business and add new business logic, while establishing and maintaining their warehouse as a single source of truth.",[],{"_key":490,"_type":255,"children":491,"markDefs":496,"style":263},"1c1d98e9bacb",[492],{"_key":493,"_type":259,"marks":494,"text":495},"9679c3bad5940",[],"Using a handful of fact and dimensional tables in the warehouse, we built dozens of modern dashboards to capture a range of diverse and complex facets of the business. We used Looker’s Git-based workflow to create and test dashboards based on constant feedback from stakeholders before going into production. With Looker’s semantic modeling layer, Byrider can standardize common metrics, definitions, data models, views, and dimensions across all user experiences. The interactive dashboards now offer new functionality and opportunities for collaboration that go well beyond static spreadsheets.",[],{"_key":498,"_type":255,"children":499,"markDefs":504,"style":263},"8f6a5bc7d8aa",[500],{"_key":501,"_type":259,"marks":502,"text":503},"3049151be3060",[],"Byrider can get both high-level summary data and granular specific data, as well as tracking and source information, within the same dashboard. Filters, windows, and interactive map options are available for displaying time series and location-related data with clear visibility to enhance user understanding. For security and access, Ollion enabled user attributes and row-level security. With these controls, the same dashboards can be accessed by multiple users, but users only have access to the data that is relevant to them. The result is custom dashboards that meet the unique business needs of Byrider and its internal teams and users.",[],{"_key":506,"_type":255,"children":507,"markDefs":512,"style":263},"18c5199bf713",[508],{"_key":509,"_type":259,"marks":510,"text":511},"01be070612350",[],"Ollion consultants also took advantage of Looker’s advanced features to incorporate logic that could not be captured in their previous reporting processes. For example, one time-sensitive dashboard needed to track the number of business days remaining ahead of a set deadline. Byrider struggled to define business day logic in their old system and used calendar days instead, resulting in inaccurate measures. To solve this problem, Ollion created a lookup table in Looker using its derived table feature. This allowed the dashboard to track remaining business days instantly and reliably, as intended. 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