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Big data analytics services
& solutions we provide

Our big data analytics services

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Consulting

Within the scope of our big data analytics consulting services, we develop comprehensive strategies for implementing, migrating, and optimizing big data analytics solutions and guide companies through big data analytics projects from start to finish.

  • Definition of a company’s analytics and reporting needs
  • Big data use case identification
  • Audit of a company’s data infrastructure and data management processes
  • Big data analytics solution conceptualization
  • Tech stack advisory
  • Advising the company on big data architecture design, as well as big data analytics solution development/configuration, customization, and integration scope
  • Developing the roadmap for a big data analytics solution implementation
  • Big data analytics project delivery oversight and advisory guidance
  • Assisting with end-user training and onboarding

Implementation

Our big data engineers and solution architects deliver a robust analytics system for turning large volumes of raw data into meaningful insights.

  • Company data landscape and analytical processes discovery
  • Defining the solution’s functional and non-functional requirements
  • Big data analytics architecture design
  • Choosing technologies for delivering the big data analytics solution
  • Building tools for data integration, analysis, storage, and visualization
  • Implementing data quality management, governance, and security mechanisms
  • User training and onboarding
  • Post-implementation solution monitoring and troubleshooting

Support & maintenance

Itransition’s support team provides post-launch solution maintenance services, ensuring the big data analytics system’s failure-free and secure operation.

  • Delivering software updates and security patches
  • Measuring big data analytics solution performance
  • Monitoring the big data analytics system for security vulnerabilities
  • Timely troubleshooting and problem resolution
  • Analyzing and reporting the usability and adoption trends of the big data analytics system
  • Implementing new functionality and integrating additional data sources on demand

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Selected success stories

A data analytics solution for a global retailer

8%

visitor-to-buyer conversion increase

A data analytics solution for a global retailer

Itransition provided a large fashion retailer with a BI platform that can process terabytes of user behavior data in near real time, as well as with an AI-powered recommendation engine for personalizing the customer experience. As a result, the client enhanced their understanding of customers and managed to increase sales while reducing analytics infrastructure costs by half.

Pharmaceutical data analytics suite for a US multinational

10x

faster data processing

Pharmaceutical data analytics suite for a US multinational

Throughout 10 years of cooperation with a global pharmaceutical market analytics company, Itransition delivered a range of solutions for analyzing, managing, and visualizing large volumes of multi-source and multi-format data, such as patient records and patent information. The solutions enable non-technical users to process data at a high speed, build sales reports, forecast inventory and revenue risks, and derive actionable insights about the market share of different drugs across countries.

BI solution for case study coverage analysis

19%

increase in leads number

BI solution for case study coverage analysis

IWe delivered a solution on top of Power BI for CTOs, heads of departments and centers of competence, and marketing teams to streamline the analysis of large volumes of case study data from various industries and projects. The solution allows users to measure current case study coverage, identify content gaps, and make informed decisions about developing new case studies to showcase relevant experience to their customers.

Hear from our customers

To help reduce the chaos and help management reduce redundancy, we decided to implement a web dashboard for data visualization, which would enable senior managers of our pharmaceutical clients to analyze various product KPIs in a much more convenient way, and gather the legacy Excel and PowerPoint reports into a structured, searchable library…The solution Itransition delivered helped us further raise the bar in the level of services we provide to our clients and allowed us to significantly increase their satisfaction and bolster our competitiveness on the market. While working on the project, Itransition’s team has proven to be responsible and experienced professionals, often acting as a valuable technology consultant, and demonstrated a highly creative, autonomous, and proactive approach.

Doug Yasso

Vice President, Data Design Consulting, Inc.

Itransition proposed and implemented the solution for Redshift structure, ETL process, and Tableau reports optimization. It took them only 2 weeks to make it all happen… Also, Itransition developed the recommendations for us on how to build a future-proof BI system.

With all said above, I’d definitely recommend Itransition as a smart and easy-to-go service provider to other companies looking for boosting their solutions built around data.

Vadym Boikov

Head of Data Science, Tasq.ai

We have formed a stable long-term partnership with mutual business goals that allowed us to develop a modern, future-proof ETL and data warehouse solution. Thanks to advanced analytical capabilities, including self-service, data delivery and reporting accelerated…We have already recommended Itransition to our partners. We will not hesitate to suggest collaborating with their BI and data warehouse experts on projects that require a professional, scalable, and highly skilled team.

Alon Kovner

Managing Director, Indigina Technologies Limited

Itransition simplified our lives significantly. In a couple of weeks, they delivered an ETL solution reducing manual intervention and streamlining the entire reporting process from several days to just a minute… Itransition is a flexible and responsive partner with extensive technology and domain knowledge, which enables them to suggest the most efficient options in every particular case. With their quick response and delivery, they are the best partner to help with the prompt resolution of business challenges related to data management. Therefore, I highly recommend Itransition for any time-critical projects requiring strong data management expertise and high commitment.

Richard Boultbee

Managing Director, WPS UK

We are extremely happy with the quality of Itransition work, as evidenced by the reduction in time to render the report from 60 to 1-2 seconds! It took the Itransition team only 2 weeks to optimize the embedded Power BI and enhance its maintainability. As a result, we went to production with the embed-for-clients solution quickly. Their impact didn’t stop there. They also enhanced the Power BI report design to make the navigation responsive and logical, provided support and enhancement of our .NET-based web app, and applied Azure DevOps best practices. We were consistently impressed with the skills and dedication their team employed to fulfill our business needs.

John Joseph

Head of Technology, Solomon Coyle

Key components of the big data analytics architecture we deliver

We provide a complete suite of solutions to facilitate the big data analytics process end-to-end, from integrating data from various data sources to transforming complex data into valuable business insights.

Data visualization

Data visualization

To help companies make data-driven decisions based on big data insights, we deliver interactive dashboards and reports that present analytics results in easy-to-interpret charts, graphs, and diagrams. We make sure our visualization solutions enable users to explore data from various angles, filter out details, and dig into the metrics to discover patterns, relationships, and trends.

Data analytics

We implement solutions for big data processing and equip them with advanced analytics capabilities, such as predictive analytics and prescriptive analytics, for detecting hidden patterns, market trends, correlations, and other useful insights in vast datasets and providing suggestions for enhancing business outcomes.

Data governance

To ensure big data quality, security, and availability, we set up rigorous frameworks for data storage, management, access, and disposal. Specifically, we implement strong security measures, define access rights and accountability for data assets, and ensure the big data analytics solution’s compliance with relevant data management regulations.

Our big data analytics solutions across industries

Retail & ecommerce

  • 360-degree customer view based on each person’s buying journey, preferences, in-store and online behavior, and support requests
  • Customer behavior and preferences analytics to optimize marketing campaign effectiveness, personalize customer experience, and enable proactive customer support
  • Customer sentiment identification to understand brand perception
  • Market trend forecasting for product planning and pricing optimization
  • Supply chain insights for inventory and product delivery optimization
etail & ecommerce

Healthcare

  • Predictive diagnostics based on patient vital sign data, electronic health records (EHRs), lab results, imaging, genetic data, and information from wearables and social determinants of health
  • Personalized insights into patient health data for treatment planning and care effectiveness improvement
  • Hospital data analysis to optimize medical staff, wards, and equipment allocation
  • Analysis of hospital data on equipment usage and inventory levels for predictive maintenance and timely medicine replenishment
Healthcare

Financial services

  • Detection of fraud, theft, and money-laundering activity based on real-time and historical data on transactions
  • Predictive modeling and risk assessment for lending decision-making
  • Comprehensive audience needs and competitor analytics to develop market-aligned financial products
  • Portfolio performance analysis and financial returns forecasting for smarter investment planning
Financial services

Insurance

  • Customer data analysis, risk assessment, and insurance event prediction for underwriting decision-making
  • Structured and unstructured claims data analytics for accurate claims assessment and fair compensation decisions
  • Fraudulent claims detection
  • Prescriptions on optimal insurance premiums and claim approval or denial decisions
  • Customer behavior and satisfaction analysis for customer churn and lifetime value prediction
  • Forecasting of a company’s cash flow and overall financial health
Insurance

Real estate

  • Property sales trends analysis and prediction
  • Forecasting of demand for specific properties and neighborhoods
  • Generation of personalized property recommendations
  • Property value, profitability, and investment risk forecasting
  • Off-market property opportunity identification
  • Construction project monitoring, including property availability, price trends, and progress analysis, based on publicly available information
Real estate

Manufacturing

  • Product quality analysis and comparison against set benchmarks based on data received from plant sensors, scanners, and quality tracking software
  • Individual employee and overall shift performance analytics
  • OEE analysis and predictive maintenance planning based on equipment data
  • Material inventory levels analysis and forecasting for timely replenishment
  • Analyzing employee and equipment data to monitor workplace safety levels, compare safety metrics with expected levels, and investigate work-related incidents for root cause analysis and prevention enablement
  • Asset usage and location data analytics to prevent loss and downtime and optimize resource allocation for maximum utilization
Manufacturing

Software & hi-tech

  • Comprehensive user journey analytics to identify drop-off and friction points and create a plan for improving the product experience
  • Customer churn prediction
  • Fraud detection based on user activity and transaction data analysis
  • Customer preferences and usage history analysis for marketing offers personalization
  • Market intelligence and competitor benchmarking for product gaps detection
Software & hi-tech

Telecom & media

  • Network performance analytics to detect potential bottlenecks like high response latency or timeouts and prevent service disruptions
  • Predictive maintenance planning based on comprehensive asset data
  • Customer sentiment and preferences analysis for suggesting relevant media content
  • Ad placement insights
  • Public sentiment and market trends analysis to develop demand-driven content
  • Identification of fraud, subscription abuse, and identity theft
Telecom & media

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Why choose our big data analytics services

Profound expertise

As part of our company-wide R&D program, we have competency centers where our specialists constantly deepen their knowledge of different technologies, including artificial intelligence and data analytics, to deliver robust, future-proof big data analytics solutions meeting the needs of various customers.

Flexible partnership options

We offer diverse engagement models for various project needs. We provide dedicated specialists or teams that can join your in-house team or offer end-to-end project execution, assuming full responsibility for the entire project scope. Moreover, we can accommodate different budget management requirements, offering time-and-material and fixed-price models for both unchanging and evolving project scopes.

Development agility

When delivering big data analytics solutions, we adhere to Agile best practices, ensuring fast value delivery, continuous solution improvement, and ongoing, close collaboration with your team to align the product with your expectations. We offer full project transparency, as well as timely mitigate emerging risks, making sure that the project runs smoothly while maintaining product quality.

Technologies & tools we work with

Data integration & quality management

AWS Glue

Databricks

Informatica PowerCenter

Microsoft SQL Server Integration Services (SSIS)

MuleSoft Anypoint Platform

Oracle Data Integrator

Pentaho

SAS Data Management

SnapLogic

Striim

Talend

Amazon

Amazon Data Firehose

Amazon DataZone

Apache

Apache Airflow

Apache NiFi

Microsoft Azure

Azure Data Factory

Azure Event Hubs

Azure Stream Analytics

IBM

IBM DataStage

IBM InfoSphere

SAP

SAP Business Object Data Services (BODS)

SAP Replication Server

Data storage

IBM Cloud Object Storage

Microsoft SQL Server

MongoDB

MySQL

Neo4j

PostgreSQL

Snowflake

Teradata

Amazon

Amazon DocumentDB

Amazon DynamoDB

Amazon RDS

Amazon Redshift

Amazon S3

Apache

Apache Cassandra

Apache CouchDB

Apache HBase

Microsoft Azure

Azure Blob Storage

Azure Cosmos DB

Azure Data Lake

Azure SQL Database

Azure Synapse Analytics

Google Cloud

Google BigQuery

Google Cloud Datastore

Google Cloud Storage

Data analytics

Matlab

PySpark

R

Scala

Amazon

Amazon Athena

Amazon Redshift

AWS Glue DataBrew

Amazon Kinesis Data Analytics

AWS Lambda

Amazon EMR

Amazon OpenSearch Service

Apache

Apache Spark

Apache Hadoop

Apache Kafka

Apache Flink

Microsoft Azure

Azure Synapse Analytics

Azure Data Explorer

Azure Stream Analytics

Azure Event Hubs

Azure HDInsight

Azure IoT Hub

Azure Analysis Services

Azure Machine Learning Studio

Google Cloud

Google BigQuery

Google Cloud Dataprep

Google Cloud Dataflow

Pub/Sub

Cloudera

Cloudera Data Platform

Databricks

Databricks Unified Analytics Platform

Microsoft SQL Server

Microsoft SQL Server Analysis Services (SSAS)

Power BI

SAS

SAS Visual Analytics

SAS Enterprise Miner

IBM

IBM Cognos Analytics

IBM SPSS

Data visualization

GrafanaDatawrapper

Infogram

Metabase

Redash

FusionCharts

Amazon

Amazon QuickSight

Microsoft
Microsoft Power BI
Salesforce/Tableau
Tableau
Qlik

QlikView

Qlik Sense

Google

Looker

Looker Studio

Google Charts

SAP

SAP Analytics Cloud

IBM

IBM Cognos Analytics

JavaScript libraries

D3.js

Chart.js

Highcharts

Open source platforms

Apache Superset

Plotly

Chartist.js

Python

seaborn

bokeh

Altair

Matplotlib

Plotly

R

ggplot2

Shiny

JavaScript

Three.js

Vega-Lite

Cloud solutions

Klipfolio

Zoho Analytics

BI integrations

Tableau Public

Microsoft Power BI Embedded

Data security management

Apache ZooKeeper

Google Secret Manager

Amazon

AWS Cognito

AWS Identity & Access Management (IAM)

AWS KMS

AWS CloudHSM

AWS Network Firewall

AWS Shield (for DDoS protection)

AWS Secrets Manager

Parameter Store

Microsoft Azure

Azure Active Directory

Azure Role-Based Access Control (RBAC)

Azure Key Vault

Azure Disk Encryption

Azure Firewall

Azure VPN Gateway

Azure DDoS Protection

Google Cloud

Google Identity & Access Management (IAM)

Google Cloud Key Management Service (KMS)

Google Cloud Armor

Virtual Private Cloud (VPC) Firewall

HashiCorp

HashiCorp Vault

Terraform Cloud Secrets Management

International security standards

Regulatory requirements:

GDPR

CCPA

HIPAA

Certifications:

ISO 27001

SOC 2

Artificial intelligence & machine learning

Salesforce Einstein

Amazon

Amazon SageMaker

Amazon Rekognition

Amazon Lex

AWS DeepLens

AWS Comprehend

Amazon Polly

Amazon Transcribe

Microsoft Azure

Azure Cognitive Services

Azure Machine Learning

Azure Applied AI Services

Azure Bot Service

Azure Form Recognizer

Azure Language Understanding (LUIS)

Azure Text Analytics

Azure Speech Service

Google Cloud

Google AutoML

Google Dialogflow

Google Vision API

Google Cloud Speech-to-Text

Google Cloud Natural Language AI

Google Cloud Speech-to-Text

Google Text-to-Speech

Common libraries

TensorFlow

PyTorch

Scikit-learn

XGBoost

CatBoost

Python ecosystem

Keras

LightGBM

Statsmodels

Natural language processing

SpaCy

NLTK

Hugging Face Transformers

Graph neural networks

DGL (Deep Graph Library)

PyG (PyTorch Geometric)

Need help implementing a big data analytics solution?

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Big data analytics challenges we help solve

Given the complex nature of big data analytics, the adoption of an infrastructure to process and manage it can present some challenges to companies. Here’s how our specialists help companies navigate common project risks, ensuring smooth implementation and long-term efficiency of the solution.

Concerns

How we help

High costs
Big data analytics projects entail lots of expenses, from purchasing new hardware and software licenses to hiring solution consultants and developers, data analysts, and project managers, as well as paying for the development, setup, configuration, maintenance, and evolution of the new software. For this reason, some businesses delay the implementation of a big data analytics solution.

At Itransition, we are proficient in implementing open-source data processing and management solutions, allowing you to eliminate upfront expenses on software licenses. We can also implement serverless solutions, enabling you to reduce costs for installing hardware for a big data analytics system. Additionally, we can select suitable solutions with pay-as-you-go pricing models, ensuring that you pay only for the resources that you need to perform your current analytical tasks. Finally, our specialists craft tailored resource optimization strategies, including hierarchical storage management and right-sizing compute instances, to help you avoid unnecessary spending.

Solution scalability & performance
Big data is associated with large volumes of information that can increase rapidly, extending the capacity of the current analytics infrastructure. The challenge lies in ensuring the big data analytics system’s scalability to handle changing data volumes and robust performance under increased workloads.

We select suitable cloud-based big data solutions that can automatically provide more computing and storage resources in response to increased demands. To ensure low-latency big data processing, we leverage techniques such as load balancing, data caching, and asynchronous and parallel data processing. We also enable efficient network communication with the help of connection pooling, data compression, and protocol optimization to improve data query performance and reduce processing time. Besides, we implement in-memory processing solutions and optimize database queries to increase data retrieval speed.

Lack of internal technical expertise
Properly utilizing big data analytics solutions can be challenging for employees who lack more technical analytical skills and are accustomed to the analytical and reporting processes and tools previously in use. As a result, they may struggle to convert big data into valuable insights, which can prevent the company from achieving the anticipated ROI of the big data analytics solution.

Apart from delivering big data analytics solutions, we organize role-based training programs and create user guides to help your employees master the proper usage of the big data analytics system. We also equip big data analytics solutions with user-friendly interfaces and self-service analytics capabilities like support for natural language data exploration, AI-powered suggestions, and customizable report templates to lower the solution’s learning curve and reduce business users’ reliance on IT teams for data analysis tasks.

FAQs

Big data analytics refers to the process of analyzing data sets that are too large, varied, and fast-changing for traditional data analytics systems to handle. Big data analytics solutions rely on statistical, mathematical, and machine learning algorithms to process large datasets and provide hidden patterns, insights, and correlations that allow companies to improve their business processes and overall performance.

According to statistics on the future of big data, the demand for dedicated solutions that help businesses make sense of the ever-expanding data will grow in the upcoming years. Big data analytics software helps companies process large and complex datasets and get a complete and up-to-date view of their performance, business operations, market trends, customers, and competitors. Based on these deep insights, companies can make smarter tactical and strategic decisions, uncover new business opportunities, drive innovation, and boost their operational efficiency.

The cost of implementing a big data analytics solution depends on a business’s existing data management environment, the system’s functionality, including self-service capabilities, and user roles, the need for custom coding, hardware setup expenditures in case of on-premises implementation, and licensing fees for cloud-based services. Costs start at $40,000 for simpler projects and increase as the planned solution becomes more advanced. To obtain a ballpark estimate for your big data project, you can schedule a free consultation with our experts now.

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