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.
Cases
Since 2018 we develop customized data engineering solutions for clients with diverse business needs.
All Cases ⤴
Links to industry-specific information and cases
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E-commerce
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iGaming
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Web 3.0
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SaaS
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Crypto
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Social Discovery
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
FAQ
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How do you approach data integration from multiple sources?
We employ a comprehensive approach to data integration, utilizing advanced ETL (Extract, Transform, Load) processes and modern data integration tools. Our team assesses your existing data sources, designs a unified data model, and implements robust pipelines to consolidate data from diverse systems. We ensure data quality and consistency throughout the integration process, enabling a single source of truth for your analytics and decision-making needs.
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How can Dot Analytics data engineering services enhance my organization’s decision-making processes?
Our data engineering services ensure that your business decisions are based on accurate, high-quality data. We help you collect, integrate, and process data to gain insights faster.
Let us do this voluminous and labor-intensive work, which reduce manual efforts, allowing your teams to focus on strategic actions. -
I could’ve just bought a connector from Airbyte, Segment, MeasureSchool, Coupler, Fivetran — you name it.
As you can see, there are plenty of vendors offering these kinds of plug-and-play tools. But do they really understand what you need from your data? These solutions aren’t tailored — they give you raw data, and the rest is your problem. If working with raw data excites you — send us your CV.
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What kind of ongoing support does Dot Analytics provide after data solution deployment?
We offer continuous support to keep your data infrastructure running smoothly. Our maintenance services include governance, data quality management, cataloging, and lineage tracking. We also provide updates, performance optimizations, and enhancements to align with your evolving business needs. With our proactive approach, we ensure your data solutions remain scalable, secure and future-proof.
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What are the benefits of outsourcing data engineering?
This allows you to get expert knowledge in ETL, transformation services and cloud data management from Dot Analytics. Our solutions guarantee high-quality results in a short time, without the need to hire employees.
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How do I get started?
Getting started is easy. Reach out to us with your needs, and our data engineering consultant will tailor data processing solutions to transform your data into a valuable asset.