Data scattered across systems
Sales, marketing, warehouse and product each store data apart, and any report means bringing it together by hand.
Big Data
Data you can actually work with
We build warehouses and pipelines for large volumes. Data from every system becomes available for analytics and models.
A normal database can't cope
There is so much data that queries take hours, reports stall, and the product database suffers from analytical queries.
Decisions need fresh data
The business needs decisions on fresh data, for monitoring, pricing and fraud checks, while data still refreshes once a day.
A map of sources, volumes and how fresh the data must be
Warehouse architecture and technology chosen for your volumes
Pipelines from databases, APIs, logs and events
Batch and stream processing of the data
A warehouse in BigQuery, PostgreSQL or Elasticsearch
Data quality checks and pipeline monitoring
Analytics access: data marts and a link to BI tools
PROCESS
[ 01 ]free · 30 min
[ 02 ]14 business days
[ 03 ]depends on scope
[ 04 ]ongoing, monthly cycle
From request to result
[ 01 ]free · 30 minClarity Session
We review the data sources and the jobs they should solve. You leave with the key constraints. No sales pitch.
[ 02 ]14 business daysAudit and architecture
A map of sources, volumes, requirements and warehouse design. You get a plan, a timeline and an estimate.
[ 03 ]depends on scopeBuild
We set up pipelines and the warehouse in stages, starting with the sources the business needs most.
[ 04 ]ongoing, monthly cycleSupport
Pipeline monitoring, new sources, and control of processing and storage costs.
Frequently asked questions
and answers
How is Big Data different from Data Analytics?+
Big Data is the infrastructure: how to collect, store and process large volumes from many sources. Data Analytics works with data already prepared: reports, dashboards, answers to business questions. Without infrastructure, analytics drowns in manual consolidation. Without analytics, the infrastructure delivers no value.
Do we really need Big Data?+
Not necessarily. Many companies are fine with a well set up warehouse on a regular database and a BI tool. A complex Big Data architecture is needed when volume, arrival speed or the number of sources no longer fit simple solutions. We say this plainly after the audit.
What will storage and processing cost?+
It depends on volumes, refresh frequency and the technologies chosen. At architecture stage we forecast the cost for your volume and build in control. Inefficient queries and excess storage often cost more than the infrastructure itself.
Do our systems have to stop to be connected?+
No. Collection is set up so it does not load live systems: through replicas, change logs or an API. The product and the team keep working while the warehouse is built.
THE FINAL STEP TOWARD A SYSTEMReady to turn growth
Ready to turn growth
into predictability?
Start with a free 30-minute Clarity Session.
