Analytics Process Automation

Problems We Solve

Manual Data Collection From Multiple Sources

Pulling data from your CRM, ad platforms, product analytics and databases by hand before any analysis takes up time that should go to the analysis itself. RPA collects and consolidates data automatically on a schedule.

Recurring Report Assembly

Building the same weekly or monthly report by hand, even when the structure never changes, is a drain on the analytics team. Automated reports run on schedule and deliver to the right people without anyone touching them.

Dashboard Refresh Delays

Dashboards that only get updated when someone manually runs the pipeline mean decision-makers are always working with slightly stale data. Automated refresh keeps them current.

Data Transformation Bottlenecks

Raw exports that require manual cleaning and reformatting before they can be used slow down every analysis. RPA handles standard transformation steps automatically as data comes in.

Data Source Integration

We connect your analytics stack, data warehouse, CRM and marketing platforms so data flows in automatically without manual exports. Common tools include BigQuery, Snowflake, Salesforce, Google Analytics and Looker.

Reporting and Pipeline Automation

Recurring reports, dashboard refresh pipelines and data transformation workflows run on automated schedules so your team always has clean, current data to work with.

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Analytics Challenges RPA Solves

More time for analysis

When data collection, transformation and report delivery run automatically, your analytics team recovers hours every week that currently go to data plumbing, and those hours go back to actual analysis.

Always-current dashboards

Automated pipelines mean stakeholders work with fresh data, not a snapshot from Monday that someone will update when they have time.

Faster time to insight

Removing the manual steps between raw data and a usable report means your team can answer questions faster and spend less time on the mechanics of getting data into shape.

Our Development Process

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Discovery Call

Initial consultation. Project assessment. Solution overview.

Strategy & Proposal

Refine project scope. Define clear goals. Deliver tailored solutions.

Integration

Optimize workflows. Enhance collaboration. Accelerate growth.

Support, Monitor & Scale

Maximize uptime. Ensure peak performance. Drive continuous improvement.

Implemented
Workflows

NDA

AI-Powered Recruitment Automation for Affiliate Marketing

Workflow Automation

AI Implementation

A four-module AI layer that took a high-velocity affiliate marketing recruiting team from manual notes and ad hoc sourcing to standardised briefs, evaluations and branded assets, live in four weeks.

AI-Powered Recruitment Automation for Affiliate Marketing

NDA

AI-Powered Recruitment Admin Automation

Workflow Automation

AI Implementation

Recruitment

A lightweight n8n and AI pilot that took a two-person UK recruitment boutique from manual notes, CVs and follow-up tracking to a fully automated admin cycle, delivered in five working days.

NDA

AI-Powered Lead Generation Platform

AI Implementation

Sales Automation

Sales

A custom outbound platform that replaced four disconnected tools with one AI-orchestrated pipeline for a UK recruitment consultancy, turning hiring signals into qualified conversations without the manual legwork.

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What clients say about us

They are truly experienced specialists who work in a well-coordinated way.

Sidis Group has delivered around 15 well-tested features, saving the client approximately 100 man-hours. The team has a well-structured process and communicates effectively. They're also professional, experienced, and organized. Overall, the client is very satisfied with Sidis Group's work.

Nikolay Popov

Head, AdKey.app

There have never been any critical issues with timing or estimation.

Sidis Group has launched the client's MVP within the agreed timeline and budget. The team has deployed the platform into production with live users and improved operational efficiency due to optimized business processes. Moreover, Sidis Group has integrated key third-party providers.

Denis Gulagin

CEO & Founder, Bakksy

Their genuine interest in the project was most impressive.

Sidis Group's completed the project quickly and on time. The team responded promptly to requests and handled all adjustments efficiently throughout the project. Moreover, they were highly engaged, proactive in suggesting improvements, and committed to achieving optimal results.

Dmytro Kaminskyi

IT Support Engineer for E-Commerce & Amazon, I'm a Natural

GET IN TOUCH

Fill out our contact form for a free consultation, or book an online meeting directly via Calendly.

We discuss your project even if you have just a raw idea.

We choose a model and approach that are suitable for your case and budget.

Questions & answers

What analytics tasks can RPA automate?

Data collection from multiple sources, standard transformation steps, report generation, dashboard refresh scheduling, KPI tracking and recurring data exports. Anything that runs the same way on a regular schedule is a strong candidate.

Which analytics platforms and data tools can you integrate with?

We have connected workflows with BigQuery, Snowflake, Redshift, Looker, Tableau, Power BI, Google Analytics, Salesforce and various marketing data sources. If it has an API or export capability, we can usually work with it.

Is this the same as building a data pipeline?

There is overlap. For structured, engineering-led data infrastructure, we build proper pipelines. For repetitive, process-based data work that sits outside the core data stack, RPA is often faster and more flexible.

How do we make sure the automated data is accurate?

We build validation checks into every workflow so anomalies get flagged rather than passed through. Every automated action is also logged for traceability.

How long does implementation take?

A single reporting automation or data collection workflow can go live in one to two weeks. A broader analytics automation program usually takes four to eight weeks depending on the number of data sources.