Webshark delivers data analytics services for companies that collect plenty of data but struggle to use it. As a data analytics company with engineers, analysts and data scientists under one roof, we connect your sales, marketing, finance, operations and product data, then turn it into dashboards, forecasts and insights your teams act on every week. Our data analytics consulting covers strategy, KPI design, reporting, predictive models and big data analytics services, using Power BI, Tableau, Looker, Python, SQL, Snowflake, Databricks and BigQuery. Every engagement follows ISO 27001 certified security and CMMI Level 3 delivery processes. Need the pipelines behind the dashboards? See our data engineering services.
Years of Software Engineering Experience
Projects Delivered Across Industries
Countries Served, Including the USA
Active Clients Trusting Our Engineering
Every data analytics engagement follows ISO 27001 certified security and CMMI Level 3 delivery processes, with data handling aligned to GDPR, CCPA, HIPAA and the industry standards your auditors expect.
From a first KPI dashboard to enterprise-wide analytics, our data analytics services cover strategy, reporting, advanced analytics and data science.
We start with the decisions you need to make, then design the data, models and reports that support them.
Analytics strategy, KPI frameworks, tool selection and a roadmap tied to business goals.
Power BI, Tableau and Looker dashboards with automated, trusted reporting.
Forecasting, churn, demand and risk models built with machine learning.
Analytics on large and streaming datasets with Spark, Databricks and Snowflake.
Attribution, segmentation, lifetime value and campaign performance analysis.
Governed semantic models and training so teams answer their own questions.
Analytics only creates value when people trust the numbers and use them. That is what our data analytics company designs for.
Our data analytics consulting begins with the decisions your leaders make each week, not with tools. We define KPIs with clear owners and formulas, agree a single source of truth and design reports around real workflows. The result is analytics that gets opened every Monday, not dashboards nobody remembers.
Many analytics projects fail because the data underneath is messy. Our data engineers, analysts and data scientists work as one team, so pipelines, models and dashboards fit together. You get a data analytics company that can fix the foundations and deliver the insight on top.
A proven approach takes you from scattered spreadsheets to trusted, automated analytics.
Every data analytics engagement begins with discovery and KPI design. We interview stakeholders, map the decisions they make each week and agree the KPIs, definitions and targets that genuinely matter. We also audit existing reports, spreadsheets and data sources, so the data analytics roadmap builds on what you already have. You leave this step with a KPI dictionary and a prioritized list of business questions to answer.
Next we audit and prepare your data. We assess quality, completeness, freshness and access across systems such as your ERP, CRM, ecommerce platform, marketing tools and databases, then clean, join and model the data needed for analysis. Where reliable pipelines are missing, our data engineers build them with automated tests and monitoring, so dashboards and models are based on numbers your team can trust.
We then design your analytics architecture: data warehouse or lakehouse, semantic layer, BI tool and data science environment. Each choice is made against your data volumes, team skills, security needs and budget, whether that means Snowflake, BigQuery, Databricks or a leaner setup. Everything is documented with diagrams and naming standards, so your own team can maintain and extend the analytics stack confidently after handover.
Our analysts build dashboards and scheduled reports with clear visuals, sensible drill-downs, filters and row-level security, so each person sees exactly the data they should. Every dashboard is tested with real users before rollout to confirm it answers the questions it was built for and loads quickly. Executives, managers and operational teams each get views designed around the decisions they make every day.
Where it adds clear value, our data scientists move beyond reporting into advanced and predictive analytics. We build forecasting, customer segmentation, churn prediction, pricing and anomaly detection models in Python, validate them against historical data and explain results in plain language. Models are connected to dashboards and business workflows, so predictions lead to actions such as reorder alerts, retention campaigns or fraud reviews.
Insights only matter when people use them, so adoption is part of our data analytics services. We train business users and analysts on self-service reporting, write simple guides and run office hours after launch to answer questions. Usage metrics show which dashboards are used and which are ignored, so we can improve the useful ones, retire the rest and keep the reporting estate focused and trusted.
After launch our team keeps your analytics running smoothly. We monitor data refreshes and pipeline health, fix issues quickly, add new metrics and data sources, and tune query performance and cloud cost as data grows. You can keep Webshark as your long-term data analytics partner on a monthly plan, or hand over to an internal team with full documentation and a structured knowledge transfer.
Business questions, KPIs and roadmap.
Quality checks and clean, modelled data.
Warehouse, semantic layer and BI tool.
Tested dashboards with drill-downs.
Forecasting and ML models.
Training, guides and usage tracking.
Ongoing support and improvements.
Our data analytics company works with ecommerce, fintech, healthcare, logistics, manufacturing and SaaS businesses.
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Each industry has its own KPIs, data sources and rules, and we design analytics around them.
Answers to the questions teams ask before hiring a data analytics company: cost, tools, timelines and results.
Data analytics services help businesses collect, clean, analyze and visualize data so leaders can answer questions and make better decisions. They typically include data analytics consulting, KPI design, data preparation, dashboards and reporting, predictive analytics, big data analytics and data science. A good data analytics company connects these pieces, so insights are based on trusted data and lead to clear actions like cutting costs, improving conversion or reducing churn.
Data analytics services are priced by scope. A focused dashboard or reporting project usually costs $8,000 to $30,000. A full data analytics program with data preparation, several dashboards and predictive models typically ranges from $35,000 to $120,000. Ongoing support and enhancements are available monthly. The main cost drivers are the number and quality of data sources, data volumes, the number of dashboards and models, and security or compliance requirements.
A first set of dashboards can usually be live in 4 to 6 weeks, provided data access is available early. Larger data analytics programs with several data sources, a new warehouse and predictive models typically take 3 to 5 months, delivered in phases so you see value early. Data quality is the biggest factor affecting timelines, which is why we audit and prepare data before building reports.
Business intelligence focuses on reporting what happened, using dashboards, KPIs and scheduled reports. Data analytics goes further, exploring why something happened and predicting what is likely to happen next using statistical analysis and machine learning. Most organizations need both: BI for day-to-day visibility and advanced analytics for deeper questions like forecasting demand or predicting churn. Webshark delivers both, built on the same trusted data foundation.
Our data analytics team uses Power BI, Tableau and Looker for dashboards, Python, R and SQL for analysis and modeling, and Snowflake, Databricks, BigQuery and Redshift for data warehousing. We use dbt for data transformation, Airflow or cloud-native schedulers for pipelines, and native AWS, Azure and Google Cloud analytics services. We recommend tools based on your existing licences, team skills, data volumes and budget.
Webshark has delivered 580+ projects for 280+ active clients in 18+ countries over 7+ years, under ISO 27001 certified and CMMI Level 3 processes. Our data analytics consulting team works alongside data engineers and AI specialists, so insights rest on reliable pipelines rather than fragile spreadsheets. We focus on business questions first, explain findings in plain language and make sure dashboards are actually adopted, not just delivered.
Yes. Dashboards and KPI reporting are a core part of our data analytics services, built in Power BI, Tableau or Looker with drill-downs, alerts and role-based security. We design dashboards around decisions, test them with real users and train teams to use them confidently. For organizations that mainly need structured reporting and executive dashboards, our dedicated BI offering is a strong starting point. See our business intelligence services page.
Yes. Our big data analytics services handle large and streaming datasets using Spark, Databricks, Snowflake and Kafka, so you can analyze billions of rows of transactions, events, logs or IoT data quickly and cost-effectively. We design partitioning, storage formats and compute scaling carefully to keep queries fast and cloud bills under control, and we add real-time dashboards where live visibility matters.
Beyond analytics tools, our wider engineering team builds data-driven applications with React, Next.js and Angular on the front end and Node.js, Python, Java Spring Boot and .NET on the back end, deployed on AWS, Azure and Google Cloud. This lets us embed dashboards and predictions directly into your customer portals, internal apps and workflows, rather than leaving insights trapped inside a separate BI tool.
You do. All data models, SQL and Python code, dashboards, pipeline configurations, documentation and infrastructure scripts created during your data analytics project belong to you. We sign NDAs before discovery starts, work with least-privilege access to your data and follow ISO 27001 certified security practices throughout. At handover your team receives everything in your own repositories and BI workspace, with no lock-in to Webshark.
Yes. Besides fixed-scope projects, you can hire dedicated data analysts, data engineers and data scientists on monthly contracts, from one specialist to a full analytics team with a project manager. Dedicated team members work in your tools and processes with time-zone overlap, and you can scale up during major initiatives or down once reporting is stable. See our hire full-stack developers page.
Yes. After launch our support plans cover data refresh monitoring, pipeline fixes, dashboard updates, new metrics and data sources, performance tuning and model retraining, with response times agreed upfront. Our team overlaps with US business hours, and monthly reports show data health, dashboard usage and improvements made, so your analytics stays accurate and useful as the business and its data keep growing.