Data Analytics Services.

Cooperation Models We Offer

We support companies that would like to own their analytics solution, such as in-house. We also support the companies that prefer relying on a trusted outsourcing partner, skip the technicalities part and just enjoy the insights. Therefore, we offer two cooperation models:

Data analytics solution implementation

Implementing a data analytics solution

Under this model, we provide our customers with an enterprise-wide analytics solution consisting of a data lake for big data, a data warehouse, and reporting. As a result, the customer owns the solution and can continuously benefit from the insights it produces.

Data analysis outsourcing—————————

Data analytics outsourcing

In this case, our customers share their data with us and we take care of the rest – data quality management, infrastructure and data analysis. When the analysis is done, we provide the customer with a detailed report containing the findings and the recommendations on how to improve the status quo.

Services We Render

ScienceSoft supports businesses on their data analytics journeys by preparing the data and the environment, as well as applying different types of analytics to provide businesses with actionable insights.

Milestone 1. Laying the foundation

Hash Analytic team sets up a data governance strategy and develops rules and policies to ensure high data quality and proper master data and metadata management. We extract traditional and big data from multiple external and internal sources and clean it to create a solid foundation for future insights.

At this stage, we design and implement a data lake for big data (if required) and a data warehouse, as well as consult our customers on all implementation-related issues.

Milestone 2. Getting insights

At this stage, Hash Analytic team implements OLAP cubes and reporting, wisely mixes descriptive, diagnostic, predictive and prescriptive analytics to enable businesses to find out issues and their root causes, identify trends and predict how they are likely to develop or even get the hints from the analytical system on the actions to take. Besides, we organize training so that end users could make the most of the analytics solution in their daily work.

We also apply data science with its machine learning and deep learning techniques to run experiments on data, build probabilistic models, search for hidden patterns and dependencies and provide companies with extra insights.

The end of the journey: Making fact-based decisions

Applied to various business areas, an analytics solution contributes to fact-based decision-making.

Customer analytics

Customer analytics helps to understand customers’ preferences, measure their response to promotions, as well as to price and product combinations.

Marketing analytics

Marketing analytics helps to measure the success of marketing activities, identify market trends, benchmark against competitors, and analyze a product portfolio.

Sales analytics

Sales analytics helps to check accounts by type and country, latest opportunities and wins, product performance and more.

Ecommerce analytics

Ecommerce analytics helps to conduct a complete customer analysis: segmentation, engagement with products, basket analysis, customer journey analysis, forecast customer demand, analyze the performance of categories, brands and SKUs, implement ‘you-may-also-like-it’ functionality.

Performance analytics

Performance analytics helps to conduct plan/actual analysis, monitor strategic, departmental and individual metrics and always be up-to-date with the progress achieved.

Financial analytics

Financial analytics helps to solve specific financial tasks like effective cash flow and working capital management, as well as contribute to establishing a true partnership between business managers and CFOs.

HR analytics

HR analytics helps to measure staff turnover, identify the ways of fostering engagement and improve employee productivity, conduct recruiting analysis from different perspectives, as well as enable talent management analytics.

Operational and asset analytics

Operational and asset analytics helps to improve business processes, assess supplier- and vendor-related risks, forecast demand and optimize inventory.

Industrial analytics

Industrial analytics helps to optimize production, assure product quality, monitor equipment utilization and foster predictive maintenance.

Challenges We Solve

  • Missing reports and dashboards. We support managers with analytics solutions aimed to eliminate the guesswork in their decision-making and create a healthy environment for self-service analytics.
  • Delays in reporting. Understanding that timely analytics is a must for successful companies, our team is ready to deliver regular and ad hoc reporting based on both historical and real-time data.
  • Lack of data available for analysis. We believe that business intelligence should provide a full picture at any moment. That is why we take care of integrating data, even if it’s of high volume and unstructured.

Select Data Analytics Services that Suit Your Business Needs

Our proficient team is ready to deliver an analytical solution that suits our customer’s needs best. Not sure where to start? Contact us for a free consultation.