Advanced Data Analysis

Advanced data analysis service - ScienceSoft

For 29 years, ScienceSoft has been rendering advanced data analysis services. Using complex rule-based algorithms and machine learning, we bring into life predictive and prescriptive analytics to help you benefit from forecasting by spotting an opportunity or a threat well in advance.


Our data analytics achievements - ScienceSoft

  • Advanced data analysis services since 1989
  • Member of the Microsoft Partner Network since 2008
  • Microsoft Gold Data Analytics and Data Platform competencies
  • Member of the AWS Partner Network since 2017

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As every our customer has specific needs, we offer different approaches to data analysis services delivery – consulting, implementation, maintenance and support, as well as outsourced data analysis.

Delivery models of data analysis services - ScienceSoft

  • Consulting. We can help our customers solve a particular problem (or several problems). Tell us about your challenges and our consultants will scrutinize your status quo, give advice and fix the problem.
  • Implementation of a data analysis solution. We scan specific business requirements of the customer to design a conceptual solution and suggest an optimal technology stack. For implementation, we favor an iterative approach. This means that we start with developing a certain part of the solution, which allows us and our customer to repeatedly review the solution as a whole and modify it if the customer’s business requirements change.
  • Support and maintenance. We provide maintenance that covers both corrective and non-corrective actions. The latter includes adapting the analytical system to a changing business environment, expanding its functionality, fostering a proactive approach to problem management and more.
  • Outsourced data analysis. We support the customers who are willing to get insightful analytical reports and dashboards, but don’t want to implement in-house data analysis solutions. With this approach, we just need from our customers the access to their data: the team, hardware and software required to perform the task are on us. We ensure both high-quality results and safety of entrusted data, which makes ScienceSoft a perfect outsourcing partner.

Business questions we answer with data analysis

Look at the sample business questions we get from our customers and the way we answer them.

Customer data analysis

Customer data analysis

A business question: During the next promo cycle, we are planning to sell product X at a discount. How many customers would be interested in buying the product?

How we answer: We analyze historical sales of product X (taking seasonality into account) and its basket penetration. Then we scrutinize the information about customers’ response to previous promotions and deliver a sales forecast.

Ecommerce data analysis

Ecommerce data analysis

A business question: We have many visitors to our online store who do not convert into customers. Why so?

How we answer: We can design a solution that will collect the data about your online store visitors’ behavior and preferences: how they surf on your website, what products they view, what engages them. Probably, your visitors are not satisfied with your product portfolio, or maybe you need a proper recommendation engine.

Performance data analysis

Performance data analysis

A business question: What is our sales performance against the target right now?

How we answer: We can deliver a real-time KPI (key performance indicator) dashboard that shows the progress. The manager will be able to see the whole picture, as well as drill-down if they need to know the reason for underperforming or overperforming.

Financial data analysis

Financial data analysis

A business question: Should we now invest in new machinery?

How we answer: We can develop a solution to analyze cash flows and monitor how much available cash the company has. These insights, coupled with historical and expected production volume, as well as the cost of production will allow the analytical system to calculate ROI for several possible scenarios.

Marketing data analysis

Marketing data analysis

A business question: We are experiencing an increasing demand for low-fat yogurts. Is it a market trend?

How we answer: As we set up the process of data integration from multiple sources, the company can analyze both internal data (consumption patterns per customer segment, sales volume) and external (customer survey results, analysis of competitors, and official statistics on yogurt consumption) to understand the market. We also identify if this trend is typical for all customers of only for a particular customer segment.

Sales data analysis

Sales data analysis

A business question: We are a manufacturing company. What are the categories that we should prioritize?

How we answer: We analyze the total revenue split by months, revenue and income per product group, total volume produced per month, cost of the goods sold. Looking at the portfolio of categories through the lens of the income they bring and the efforts they require will help to define those to focus on.

HR data analysis

HR data analysis

A business question: Our company has been expanding very fast during the last decade, and the number of employees has been growing proportionally. Nowadays, we have HR-related information stored in different corporate systems, and we accidentally spot numerous errors there. What can we do to improve the process?

How we answer: We offer data cleansing as a part of our data analysis services. We will tune up your analytical system so that it searches for discrepancies in the data from multiple sources. According to algorithms, the system will discover typos and different abbreviations and either correct them automatically or notify the database administrator about the mismatches found.

Operational data analysis

Operational data analysis

A business question: We have a fleet of 250 trucks and often exceed fuel consumption budget. What can we do about it?

How we answer: We know how to use big data to improve your business processes. We can deliver the solution that will use telemetry data from each of your trucks, as well as weather conditions to estimate required fuel consumption and calculate optimal routes.



Our portfolio includes the projects for:

  • Banking and Financial Services
  • Healthcare
  • Manufacturing
  • Retail
  • Advertising
  • Telecom

Data-related challenges we solve

  • Low-quality data. We guard our customers against outdated or unreliable information, incomplete or duplicate data to ensure accurate reporting. We set up the process of data quality assurance to identify any anomaly and clean the data.
  • Mismatching data from different sources. We develop algorithms that help to find discrepancies among different data sources (e.g., variations in the spelling of a supplier name in different ERP modules) and make them uniform.
  • Unanswered “Why?” We help the companies that mastered descriptive analytics but faced the difficulties in understanding "Why did it happen?" to conquer diagnostic analytics.

Overview of selected technologies we use

Traditional BI technologies:

Data visualization

  • Microsoft Power BI
  • Tableau
  • MicroStrategy
  • QlikView
  • Kyubit BI
  • Sisence
  • Oracle BI

OLAP cubes

  • Microsoft SQL Analysis Services
  • Oracle BI
  • MicroStrategy
  • Sisense

Data warehouse

  • Microsoft SQL Server
  • Oracle Business Intelligence

Big data technologies:

Distributed storage:

  • Hadoop HDFS

Database management:

  • Apache Cassandra
  • Amazon RedShift
  • Apache Hive

Data processing:

  • Hadoop MapReduce
  • Apache Kafka
  • Apache Spark
  • Apache Storm

Machine learning:

  • Spark Machine Learning Library (MLlib)
  • Amazon Machine Learning

Programming languages:

  • Java
  • Scala
  • Python

Get started with insightful data analysis

Let us know your challenge, and our consultants will work out the solution that suits your needs best.

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