Ideas we realize. Problems we solve.
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Data
Tables. Sheets. Marketing data. Product data. First-party data. Historical data. Events data. Unified view. Digital footprint. Integration with existing data sources.
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Marketing data
Multiple data sources. Facebook data. Instagram data. Google Ads data. Google Search Engine data. Bing data. Matomo data. Voluum data. TikTok data. Twitch. X / Twitter data. Youtube data. Data integration. Maintenance.
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Cost efficiency
Data governance. Data infrastructure. Data architecture. Data modeling. Data organization. Data processing. Automatization. Automation. Microservice. Data security.
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Database
Data warehouse. Customer data platform. In-house database. Analytics database.
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Events tracking
Website events tracking. App events tracking.
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Data problems
Unstructured data. Large amount of data. Complex data. Faster information retrieval. Alerts. Notifications. Signals. Data mining.
Data engineering process and timeline
While the estimate depends on your project idea, we work in short, focused iterations — so you’ll see results asap. If you need help with project ideas, please read the section above.
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1
Discovery and assessment
Start of iteration 1
✔ Estimated time: 5 days.
✔ Start without the overhead of hiring in-house.
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2
Data Engineering
Execution and implementation
✔ Estimated time: 2 weeks
✔ Brainstorm
✔ Kanban
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3
Finish
Finish of iteration 1
✔ Estimated time: up to 1 week.
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4
Start
Start of iteration 2
✔ We provide support with data engineering through ongoing maintenance and other options.
Data engineering tech
Our clients
We deliver results for brands across the USA, Australia, Canada, Europe, and Asia.
We have experience and understand data in such industries: E-commerce, Social Discovery, iGaming, Web3, Healthcare, iOT, OTT, EdTech, MarTech, and FinTech.
Client testimonials
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“They did a lot of work studying real user data – they built hypotheses and ran experiments that led to a significant increase in our conversions.”
Analytics director at Plarium
Anton Polischuk
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“Dot Analytics’ work was completed on time and met our expectations. We received a ready-made infrastructure for collecting and consolidating data, moving away from manual and fragmented work.”
CTO at DataRoot Labs
Ivan Didur
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“We had so-called raw business data and we wanted to centralize it for further analysis. The main thing for us is that we got high-quality and accurate data. We are convinced that they did a great job!
CEO, co-founder of Bookimed
Yevheniy Kozlov
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“We needed to combine, process and display a large amount of data. It was a complex job and I am 99% satisfied with the result.”
CEO, co-founder at Futurra Group
Vitaliy Shatalov
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“We were interested not only in working with user data and the site, but also in comprehensively improving marketing. We are very pleased with the result.”
CEO at Kismia
Vlad Amardi
“They did a lot of work studying real user data – they built hypotheses and ran experiments that led to a significant increase in our conversions.”
Analytics director at Plarium
Anton Polischuk
“Dot Analytics’ work was completed on time and met our expectations. We received a ready-made infrastructure for collecting and consolidating data, moving away from manual and fragmented work.”
CTO at DataRoot Labs
Ivan Didur
“We had so-called raw business data and we wanted to centralize it for further analysis. The main thing for us is that we got high-quality and accurate data. We are convinced that they did a great job!
CEO, co-founder of Bookimed
Yevheniy Kozlov
“We needed to combine, process and display a large amount of data. It was a complex job and I am 99% satisfied with the result.”
CEO, co-founder at Futurra Group
Vitaliy Shatalov
“We were interested not only in working with user data and the site, but also in comprehensively improving marketing. We are very pleased with the result.”
CEO at Kismia
Vlad Amardi
Let’s get closer to the goal
The outcome is already there — now it’s time to extract it
Since 2018 we develop customized data engineering solutions for clients with diverse business needs:
✔ in-house databases, customer data platforms (CDPs) and data warehouses (DWHs).
✔ custom API connectors for integrations with marketing platforms.
✔ ETL scripts to manage data refresh.
