Manual copies
Data is copied by hand
Someone exports a file from one system and pastes it into another every week or month.
- Exports and spreadsheets
- Copy-paste between tools
Data engineering
Bring your data
together
We connect the systems your business already uses, clean the data and keep one trusted version of your numbers, so reports stop depending on manual copies.
What you get
- 1
- Trusted source for your reports
- ETL
- Pipelines that run on schedule
- 5+
- Common data stores connected
- AWS
- GCP and Azure hosting options
Sources and pipelines differ by business. We agree the first ones in the review.
What are data engineering services?
Data engineering services collect data from the systems you use, clean and combine it, and load it where reports can read it on a schedule. The result is one trusted source of numbers, so teams stop copying files by hand and stop arguing about which total is right. We connect, build, hand over and keep the pipelines running.
Is this you?
Signs you need data engineering
Conflicting numbers
Two reports disagree
Sales, finance and operations quote different totals because each team pulls from a different place.
- Different definitions of the same metric
- Time spent reconciling
One person
Only one person can pull the numbers
Reports wait on a single colleague who knows where the data lives and how to combine it.
- Knowledge held by one person
- Delays when they are unavailable
What we build
Four parts of a working data pipeline
Connect
Connect your sources
We connect the databases, applications and files that hold your data, using secure access your IT team approves.
- PostgreSQL, Snowflake, BigQuery and more
- Files and application data
Clean and combine
Clean and combine the data
We standardise names, dates and codes, remove duplicates and join records so they describe the same thing.
- Shared definitions for key metrics
- Checks that flag problems early
Load and store
Load it where reports can read it
The cleaned data lands in a store your reports and dashboards read from, updated on a schedule you choose.
- Scheduled ETL pipelines
- One version of the numbers
Run
Keep it running
We monitor the pipelines, fix failures and adjust them when a source system changes.
- Monitoring after launch
- Hosting on AWS, GCP or Azure
How we work
Start with one source and one report
You see the value early, before the work grows.
- 1
Map your data
We list the systems that hold your data and the reports people need, and agree the definitions that matter most.
- 2
Build the first pipeline
We start with one source and one report, so you see the value before the work grows.
- 3
Check the numbers
We compare the new output with the reports you already trust, and fix the differences together.
- 4
Hand over and run
You own the code and the data. We document the pipelines, train your team and agree how support works.
Questions about data engineering
It collects data from the systems you use, cleans it, combines it and loads it somewhere your reports can read. The result is one trusted source of numbers that updates on a schedule, instead of manual copies.
Not always. We look at your sources and reports, then recommend the simplest store that does the job. Many businesses start with one database and add more only when the need is clear.
Dashboards show data. Data engineering makes sure the data is complete, consistent and up to date before a dashboard reads it. We often build both, and we connect them with Apache Superset where a dashboard is the right fit.
You do. The client owns the code and its data, and Andolasoft provides the service. Documentation and handover are part of every engagement, and the way support works after launch is agreed at the start.
Request a free 30-minute review. A solutions architect replies within one business day and tells you which sources and reports to start with. We can sign an NDA before the first technical conversation.
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We will look at the sources behind them and tell you where to start. You will hear back from a solutions architect within one business day.
We can sign an NDA before the first technical conversation.