appana TechnologiesUAE · AI innovation

Data pipelines

Move data between systems without losing it on the way.

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FROM POSSIBILITY TO PRACTICE

What it does for your business

For your data and analytics team, “Data pipelines” can become a repeatable workflow rather than a separate task handled from scratch each time. AI can organise the relevant information, work through a question and prepare an explanation of the options or findings for your team. It fits into data preparation, analysis and business reporting, using your business information and the standards your team already works to.

The value it could bring

These are the improvements to evaluate against your current process. We agree the scope and test the value with your team.

More trustworthy decisions

Make the path from business data to an explanation easier to inspect, so teams can act with a clearer understanding of the numbers.

Less time assembling the picture

Bring scattered information into a useful explanation so the team can focus on evaluating the result.

Clearer reasons for a decision

Make assumptions, evidence and trade-offs visible rather than leaving them buried in separate records.

EVIDENCE FROM OTHER BUSINESSES

Published ROI evidence

These named businesses implemented related workflows. Their deployment results provide a reference for the opportunity; they are not appana projects or a promised return for your business.

Edmund Optics

Matillion with Maia

336%Reported annual deployment ROI

The organisation reported 75% faster integration development with agentic AI and more efficient delivery of unified data sets.

What the figure covers

A data-consolidation and integration-engineering deployment in Snowflake using Matillion and its agentic engineering tools.

Nucleus Research · Published 2026-06-22 · Source checked 2026-10-05

Read the published case study ↗
How the returns are assessed

Reported annual ROI uses Nucleus Research’s method: average annual net benefit across three years divided by initial investment. Assessments can include indirect benefits and projected years. Figures cover the named deployment, including software, integration and process changes; they do not isolate AI’s contribution or predict your return.

Nucleus Research’s calculation method ↗

How it works in your business

  1. STEP 1

    Bring in the right context

    Select the relevant information from your databases, spreadsheets and analytics workspace. Agree what a good result looks like with your data and analytics team, including the rules, examples and permissions the workflow needs.

  2. STEP 2

    Turn the task into a workflow

    Move data between systems without losing it on the way. Apply the agreed criteria, separate evidence from assumptions and make the reasoning available for someone to challenge or refine.

  3. STEP 3

    Put the result to work

    Provide an analysis or recommendation with supporting information, open questions and a clear decision for the owner to make. Analysts verify queries, calculations, definitions and assumptions before a result informs a business decision.

AN EXAMPLE IN PRACTICE

A member of your data and analytics team needs help with “Data pipelines”. They supply approved data sources with agreed access, together with the relevant instructions and the result they need. The workflow prepares an initial result with its supporting context, flags missing information and returns it for review. The owner can correct it and use the accepted result in the team's databases, spreadsheets and analytics workspace.

Start with a focused pilot

Choose one workflow, one team and a representative set of real tasks. We establish the current baseline, build the first version and review the results together before expanding it.

What we would start with

Depending on the scope, useful inputs include:

  • Approved data sources with agreed access
  • Metric definitions, schema and business rules
  • Known examples and quality checks

We agree access and integration with your databases, spreadsheets and analytics workspace as part of the design.

How we would measure value

  • Time to a usable, reviewed analysis
  • Accuracy of facts, calculations and supporting references
  • Reconciliation to trusted figures and time to a usable analysis

Analysts verify queries, calculations, definitions and assumptions before a result informs a business decision.

LET’S BUILD IT TOGETHER

Could this help your business?

Tell us how your team works today and what you would like to improve. We’ll explore the opportunity, shape a practical first step and build it with you.

Talk to us about this use case