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Data Engineering and Business Intelligence

Vivid Concept builds data pipelines, warehouses and reporting in Los Angeles that bring sales, marketing and operations data into one view your leadership team trusts.

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One trusted source for your numbers

Ask finance, sales and marketing for last month's revenue and you can hear three numbers, each right for its own system. Our data engineering and business intelligence work builds the pipelines, warehouse and reporting that bring those systems into one view your leadership team trusts. It is software built around your workflow, with agreed numbers as the product.

Your figures live across ad platforms, a CRM, an accounting system, a store, a booking tool and the spreadsheets that stitch them together. Each source is accurate about its own corner. The totals disagree because each system defines them its own way.

The work begins with decisions rather than tools. We ask which decisions the numbers support, who makes them and how frequently, then write each metric as a definition: what counts as a lead, when revenue is recognized, which orders are returns. Disagreements surface early, while they are cheap to settle.

Questions about systems come up along the way, such as which system should own a record. Those go to our application consulting team, whose answers keep the warehouse and your daily tools in agreement.

IN-HOUSE ADVANTAGE

Connected With Our Full Los Angeles Team

Our developers build the pipelines and the dashboards together, so the numbers on screen match the systems they come from.

What Is Included in Data Engineering and BI

One metric dictionary that finance, sales and marketing all share

Automated pipelines from your tools into a warehouse

Tested data models with quality checks and alerts

Reports for each team, built on the same definitions

Documentation, training and regular cost reviews with you

Your Data Engineering and BI Process

  1. DiscoveryWe review your setup, audience and goals, and you receive a clear scope before work starts.
  2. DesignKey choices are settled with you before work starts.
  3. BuildBuilt by our in-house team with no handoffs.
  4. LaunchEvery change is tested and reviewed by a person before it goes live.
  5. SupportThe team that built it stays available after launch.

Pipelines from your tools into a warehouse

Close-up of a hand pointing at abstract flowing lines on a monitor.

A data warehouse is a database designed for questions across many sources. It is kept apart from the systems that run the business, so analysis never slows an order. Pipelines copy data from each tool into it on a schedule or as events happen.

Most business tools offer an API, a doorway for other software, for exactly this, and our API integration team builds the connectors that managed tools do not cover. Google Analytics 4 can export raw, unsampled event data to BigQuery daily, with a streaming option for the current day, so website behavior joins sales and ad spend in one place.

Raw data is kept exactly as it arrived, and everything else is built from it. Any figure in any report can then be traced back to the record it came from.

A data engineer connects sources on a large monitor of abstract lines flowing into one block, a colleague watching.

Modeling and quality checks

Raw tables become models: a clean list of clients, orders, campaigns and tickets, joined on keys that are tested. Each model carries automated checks for freshness, duplicates, missing values and totals that must reconcile with the source system.

A failed check alerts our team before anyone reads a wrong report, and your named contact follows it through to the fix. Transformations are code in version control, reviewed like any other software, which makes every change to a definition visible and reversible.

Questions about marketing spend follow naturally. When they do, the work continues in attribution and marketing mix measurement, working from the same agreed definitions and tested tables.

Reporting each team uses

An analyst checks a clean table of clients and orders on a laptop at a tidy desk.

Finance wants closed periods, sales wants pipeline, marketing wants cost per qualified lead, operations wants backlog. Each team receives the views it needs from the same models, and a number quoted in one meeting survives the next.

Reports are built in the tool you prefer or as custom software, including dashboards built for your team where a purpose-made screen works better than a generic chart tool. Web analytics feeds the warehouse through tracking and measurement setup, making your website one more clean source.

A finance lead, a sales lead and a marketer at a table each with a different dashboard on a tablet.

Analytics and AI on top of clean data

AI becomes useful in a company once its data is clean and secure. A model answering questions about sales needs the agreed definition of sales, answers drawn only from data the person asking can already see, and a record of every query.

We prepare the warehouse for that use, then build the application, as described under building AI features into your software. The infrastructure runs on cloud infrastructure on AWS or your own provider, with budgets and alerts that keep storage and query costs visible, and we review those costs with you regularly.

Your public website can draw on the same clean data as well, and our web design and development team builds those pages on the definitions everyone has already agreed.

23 Years in Los Angeles

All Web Design & Development

Custom web applications, portals and internal tools that replace manual steps and connect your teams, scoped to your timeline and budget.

Vivid Concept builds internal tools, admin panels and live dashboards in Los Angeles that replace spreadsheets, connect your systems and show each role only what it needs.

Vivid Concept designs a measurement plan that joins GA4 attribution, consented first-party data, server-side tagging and marketing mix models into one view for budget decisions.

Data Engineering and BI Questions & Answers

What is a data warehouse and do I need one?

A database built for analysis across many sources. You need one when decisions depend on combining systems, when reports disagree, or when spreadsheets take hours to assemble. A business that runs on one tool is well served by that tool's own reports.

Which tools feed the pipeline?

Ad platforms, Google Analytics 4, your CRM, accounting, e-commerce, booking, support and billing systems, plus files and databases. Where a tool has no ready connector, we build one against its API.

How is data quality checked?

Automated tests run on every load: freshness, duplicates, missing values and totals that must match the source system. A failure raises an alert, and the affected report is flagged until it is fixed.

Can a model use this data safely?

Yes. The model reads only the tables the person asking can already see, works from agreed definitions and keeps a record of every query. Sensitive columns are masked or excluded before any model touches them.

How are costs controlled?

Storage and compute are chosen by volume, heavy jobs are scheduled sensibly, and the cloud account carries budgets and alerts. Our team watches the numbers with you, so growing data never turns into a surprise.

Tell Us About Your Project.

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