Big Data Consulting Services
Big data consulting helps derive valuable insights from vast volumes of multi-structured data relying on expert assistance. ScienceSoft offers big data advisory, implementation, support and managed services to help companies find hidden patterns, spot market trends and enhance customer understanding.
- Data analytics expertise since 1989.
- Business intelligence and data warehousing services since 2005.
- Big data consulting since 2013.
- Domain experience in 30 industries, including manufacturing, energy, retail and wholesale, professional services, healthcare, financial services, transportation and logistics, telecommunications.
Big Data Services We Offer
Big data advisory services
ScienceSoft draws up a big data implementation/evolution strategy, conceptualizes a big data analytics solution, chooses an optimal technology stack, and proves the viability of a complex big data project with a PoC.
Big data solution implementation
ScienceSoft designs, develops, and implements a full-scale big data analytics solution with a unique feature set to address your business needs and objectives.
Big data support services
ScienceSoft conducts a health check to diagnose the issues within the existing big data infrastructure, provides tailored recommendations, and introduces relevant changes, if required, to ensure maximized ROI of a big data solution and its smooth evolution.
Big data managed services
ScienceSoft aggregates and analyzes your big data so that you can get actionable one-time or regular analytics insights without the need to set up and maintain a proprietary big data solution.
The Financial Times Includes ScienceSoft USA Corporation in the List of Americas’ Fastest-Growing Companies 2022
ScienceSoft is one of 500 companies with the highest compound annual growth rate in revenue. This achievement is a result of our unfailing commitment to provide high-quality IT services and find best-value solutions to clients' needs.
Enterprise intelligence
- Enterprise data warehousing for company-wide data consolidation and storage.
- Corporate performance analytics.
- Strategic and operational planning.
Operational analytics
- Operational data storage and management.
- Detection of deviations and undesirable patterns, recognition of operational bottlenecks.
- Cause-effect analysis, operational performance prediction and forecasting.
Customer analytics
- Collection and storage of demographic, transactional, interaction, etc. customer data.
- Customer segmentation and customer behavior modeling.
- Personalized marketing, product recommendations, discounts, etc.
- Customer churn management.
Industry-Specific Solutions
Banking and insurance
- Capture and storage of data on assets and liabilities, demographic, transactional, behavioral and social data on customers and policyholders.
- Risk management (credit risk assessment, counterparty and liquidity risk analytics, etc.).
- Detecting fraud in cash transactions, check tampering, claims, etc.
- Fraud modeling.
Healthcare
- Capture and storage of patient and medical device data.
- Remote patient monitoring (alerting on acute conditions, on trends and patterns requiring a doctor’s attention).
- Personalized care and lifestyle recommendations, personalized risks assessment, etc.
Supply chain management
- Storing real-time inventory, demand, supplier, and inventory cost data.
- Demand/supply balancing in real time, inventory levels recommendations.
- Supply chain cost modeling and optimization.
- Supplier risk estimation.
Real-time asset tracking
- Collecting and storing real-time data on asset location, state (sensor readings), and usage.
- Alerting on asset misplacement, misuse, underutilization, pre-failure condition.
- Asset utilization and asset performance analytics.
Manufacturing
- Storage of equipment sensor and maintenance data, output quality data, etc.
- Predictive failure modeling in real time.
- Prediction of production defects or reduced yield.
Logistics and transportation
- Storage of real-time GPS data, cargo data (temperature, humidity), data on driver behavior, vehicle condition, etc.
- Predictive analytics for vehicle maintenance.
- Operational capacity planning (delivery schedules, labor scheduling, etc.).
- Dynamic route optimization.
Retail and ecommerce
- Storage of demographic, behavioral, psychographic, etc., customer data.
- In-store and online personalization.
- Dynamic price optimization.
- Sales channel analytics.
- Product/service performance analysis, portfolio optimization.
- Competitor benchmarking.
Telecommunications
- Storage of demographic, service usage, payment data, data on network load, failures, etc.
- Subscriber behavior analysis (subscriber segmentation, prediction of behavior, LTV and churn).
- Network management and optimization (service quality assessment, value-based network capacity planning, etc.).
Our Big Data Portfolio
Big Data Platform for Customer Analytics
- Development and implementation of a big data management platform to aggregate data from 10+ sources.
- 30-dimension ROLAP cubes for regular and ad-hoc reporting to enable:
- User engagement assessment.
- User behavior trend identification.
- User behavior forecasting, etc.
Advertising Channel Analytics Solution
- Development and implementation of a big data warehousing solution to process 1,000+ raw data types.
- A 5-module analytics system for advertising channel analysis in 10+ countries.
- Up to 100 times faster analytical query processing compared to the legacy solution.
Big Data Solution for IoT Pet Trackers
- Development and implementation of a scalable big data solution for processing 30,000+ events per second from 1 million devices for real-time location tracking.
- Customizable reports on pets’ presence.
Big Data Optimization Consulting for the Automotive Company
- Architecture redesign of the big data solution to enable collecting, processing, and storing IoT data from more than 600k connected vehicles.
- Big data tech stack selection.
- Detailed implementation roadmap for big data solution optimization.
Sales Forecasting for an FMCG Manufacturer
- Timely delivery of accurate sales forecasting and identification of sales improvement potential for up to 15% percent based on:
- A linear regression ML algorithm.
- An autoregressive integrated moving average (ARIMA) model.
- Median forecasting and zero forecasting models.
Hadoop Lab Deployment and Support
- Deployment of the on-premises Hadoop lab for student training.
- Remote assistance sessions for the Customer’s in-house team.
- Creation of comprehensive user guides.
ScienceSoft’s Experts
Alex Bekker, Head of Data Analytics Department at ScienceSoft
‘We help businesses bring their disparate big data together and turn it into actionable insights to optimize business operations, increase sales effectiveness, personalize customer experience and deliver accurate predictions.’
Mary Zayats, Lead Business Analyst and Banking IT Consultant at ScienceSoft
‘With big data solutions we help our banking clients increase efficiency in their workflows, integrate new channels for communication with their customers, and improve customer engagement and loyalty.’
Serge Pukhaev, Head of Fleet Management Practice, ScienceSoft
‘Big data technologies help capture and aggregate data from drivers, trucks and trailers to optimize fleet vehicle maintenance and improve driver’s safety, drastically decreasing downtime and maintenance costs.’
Halina Batsishcha, Healthcare IT Consultant, ScienceSoft
‘Healthcare industry provides an abundance of data – hospital records, medical devices data, biomedical research data, etc. At ScienceSoft, we help our clients manage and analyze this data properly to derive valuable insights, deliver personalized medicine and achieve improved hospital performance.’
Peter Manko, Senior Business Analysts and Ecommerce Consultant, ScienceSoft
‘ScienceSoft creates big data solutions for ecommerce companies to help them mine web browser histories, abandoned online shopping carts, social media feeds and much more – all in the pursuit of unique customer experience and increased sales.’
Our Customers Say
We needed a proficient big data consultancy to deploy a Hadoop lab for us and to support us on the way to its successful and fast adoption. ScienceSoft's team proved their mastery in a vast range of big data technologies we required: Hadoop Distributed File System, Hadoop MapReduce, Apache Hive, Apache Ambari, Apache Oozie, Apache Spark, Apache ZooKeeper are just a couple of names. ScienceSoft's team also showed themselves great consultants. Whenever a question arose, we got it answered almost instantly.
Kaiyang Liang Ph.D
Professor, Miami Dade College
Two years ago, we commissioned ScienceSoft to audit and upgrade our partially developed AI-based software for clay pigeon shooting tracking.
ScienceSoft ramped up a development team consisting of two C++ developers, two data scientists, and a UI design expert to fulfill the project. The team identified core errors, which didn’t allow efficient solution operation, and implemented high-speed convolutional neural networks to fix them. As a result, the system could track a flying target in a real-life outdoor environment and faultlessly detect shooter’s performance.
Simen Løkka
CEO, Travision AS
bioAffinity Technologies hired ScienceSoft to help in the development of its automated data analysis software for the detection of lung cancer using flow cytometry. Our project required a large amount of industry-specific methodology and algorithms to be implemented into our new software connected to EHR/LIS systems, which ScienceSoft’s team handled well due to a profound understanding of laboratory software specifics and integrations.
Maria Zannes
President & CEO, bioAffinity Technologies
We first contacted ScienceSoft to get expert advice on the creation of the centralized analytical solution. After we got a clear project roadmap, we commissioned ScienceSoft to develop a part of the solution, covering invoicing. The system automates data integration from different sources and invoice generation and provides visibility into the invoicing process. We have already engaged ScienceSoft in supporting the solution and would definitely consider ScienceSoft as an IT vendor in the future.
Heather Owen Nigl
Chief Financial Officer, Alta Resources
Unilia Canada Fuel Cells Inc. commissioned ScienceSoft to build a flexible database with user interfaces for managing our test data stored as time-based CVS files. Within 8 months, ScienceSoft delivered a fully functioning database solution regardless of the new solution requirements that appeared during the project. In the future, we are planning to extend the logic of our reports and dashboards and extend data processing options in our database solution, and we’ll definitely be considering ScienceSoft as our partner in this initiative.
Donat Gaudreau
Electrochemical Cell Design and Test Engineer, Unilia Fuel Cells
How It Works: Sample Architecture of the Big Data Solutions We Deliver
Tech Components of Big Data Solutions We Cover
ETL/ELT
Extracting data from diverse data sources, transforming it into a predefined format and loading it into a storage destination.
Identifying and eliminating data anomalies via data profiling and cleansing.
Data lake
Storing any type of data, including big data.
OLAP cubes
Structuring data in a multidimensional format for rapid self-service data analysis.
Advanced analytics with data mining, big data analysis, machine learning and artificial intelligence.
Making analytics results digestible with immersive reports and interactive dashboards.
Data security
Ensuring data is stored, transformed, and exploited securely.
Technologies ScienceSoft Works With
Data integration
Cloud data storage
Data warehouse technologies
Big data
Data visualization tools
Cloud services
Machine learning platforms and services
Machine learning frameworks and libraries
Supplementary Data Analytics Services ScienceSoft Renders
Big data database implementation
Analyzing big data storage and processing needs, designing and developing a big data solution, and integrating it into the existing technological ecosystem.
Data warehousing
DWH implementation, evolution or migration services for companies to get a scalable and cost-effective DWH and achieve transparent company-wide analytics and reporting.
Setting up the processes of secure and efficient data integration, storing, structuring and utilizing to unlock the full potential of data.
Machine learning consulting
Advising on and developing ML-powered analytics solutions to help companies find hidden patterns in massive amounts of data and enable accurate predictions and forecasting, root cause analysis, automated visual inspection, etc.
Data mining
Retrieving valuable insights out of large, heterogeneous, and constantly changing data sets.
DWH and BI testing
Validating proper BI/DWH functioning by verifying that ETL/ELT processes, DWH database and data models, OLAP cubes, BI reports and dashboards are correct and function as expected.