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      <image:title>Data Visualization - Visualize it with Omni</image:title>
      <image:caption>Braxton Analytics has experience doing Omni implementations. Leveraging Omni’s semantic layer, AI components and modern data visualization platform, Braxton Analytics can modernize your dashboard experience for your organization through Omni Analytics.</image:caption>
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      <image:title>Data Visualization - Visualize it with Looker</image:title>
      <image:caption>Braxton Analytics has deep experience developing in Looker. Leveraging Looker’s semantic layer and the LookML code to the tiles that pop out on the dashboards, Braxton Analytics is able to analyze and visualize your data within Google Cloud’s Looker product.</image:caption>
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      <image:title>Data Analytics - Analyze it with Snowflake</image:title>
      <image:caption>Braxton Analytics has experience implementing data solutions leveraging Snowflake as the underlying data warehouse. Braxton Analytics has the Professional Data Engineer Certification from Google Cloud. Whether its leveraging Push Down Optimization to take advantage of Snowflakes computing and processing power, connecting to external sources and landing data in Snowflake or doing further analytics on existing data, Braxton Analytics has leveraged Snowflake to drive value for data teams.</image:caption>
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      <image:title>Data Analytics - Analyze it with BigQuery</image:title>
      <image:caption>Braxton Analytics has experience implementing data solutions leveraging Big Query as the underlying data warehouse. Braxton Analytics has the Professional Data Engineer Certification from Google Cloud. Whether its landing data in GCP Cloud Storage, extracting data from particular endpoints and landing it in Big Query or using Big Query has the main data warehouse, Braxton Analytics drives value with Big Query as the data warehousing solution.</image:caption>
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    <lastmod>2026-04-03</lastmod>
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    <lastmod>2026-04-03</lastmod>
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      <image:title>Data Engineering - Integrate &amp; Capture data.</image:title>
      <image:caption>It all begins with the data source. How do we connect to the data? Whats the best way to connect to the data? How often is the data refreshed? Who is the main point of contact for the data source? How many endpoints do we need to connect to in order to get a full batch of data? What is the plan for if the data source goes down? Is there an existing integration tool in place or do we need to build one from scratch? Answering these questions will allow us to smoothly connect to the data at its raw source and build a sustainable infrastructure for the data pipeline to run.</image:caption>
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      <image:title>Data Engineering - Transform &amp; Load data.</image:title>
      <image:caption>What do each of the fields look like? How much logic needs to go in place in order to get the data in a consumable format? What is the plan for tracking history? Are there any nested JSON fields? What is the key structure for each table? Answering these questions are the foundation for creating a curated and reliable data set for your data team and broader organization.</image:caption>
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    <loc>https://www.braxtonanalytics.com/data-engineering-form</loc>
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    <lastmod>2026-04-03</lastmod>
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    <loc>https://www.braxtonanalytics.com/data-migration</loc>
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    <lastmod>2026-04-03</lastmod>
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      <image:title>Data Migration - Plan it.</image:title>
      <image:caption>Part of data migrations are outlining what needs to be migrated from the old platform to the new platform. Scoping out existing processes, reports, and the source tables that populate the reports is one step. Another step is outlining the tool that you are going to migrate to, why you are picking that tool and why you are leaving the old tool. Its the old saying, if you don’t know where you came from then you don’t know where you are going. Last part of data migration planning is what is the sunset plan for the old system? Is there a hard cut off date, is there a period of time where both platforms are going to run, is there a validation system in place? All of these questions need to be answered before committing to a data migration project.</image:caption>
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      <image:title>Data Migration - Migrate it.</image:title>
      <image:caption>Once the questions are answered, then development can begin on migrating off an old platform an into a new platform. You can build the pipelines, rebuild the reports, and rebuild the business processes leveraging the new system. You can also take advantage of redundant tasks and consolidate pipelines, tables and reports where necessary. This process limits technical debt and mitigates confusion within the new platform. Finally, you can start to build and enhance processes once everything is migrated and the business stakeholders feel empowered to get more insights from the data on the new platform.</image:caption>
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