Data integration services
-
Increase decision-making speed and quality with fast business insights delivered through custom data integration pipelines
-
Improve reporting and analytics by ensuring efficient data flow across on-premises, cloud-based, and external systems
-
Minimize manual data handling and improve efficiency with automated data integration processes
-
Avoid legal and reputational risks by implementing industry-compliant data integration and management flow
-
Improve cross-team productivity with varied data integration capabilities such as batch processing, real-time or near real-time data streaming
Real-life results of data integration
-
UP TO 30%
improvement in operational efficiency post-integration
-
UP TO 80%
reduction in manual data handling errors
-
UP TO 100%
compliance with industry regulations
-
UP TO 40%
faster real-time analytics
Data integration consultancy and services Yalantis provides
Yalantis data engineers build end-to-end data integration pipelines with scalability in mind. We help you identify suitable datasets to improve your analytics capabilities. Our team can ensure data integration in real time, near real time, or at custom intervals critical to your business workflow.
-
ETL/ELT development and automation
-
Writing custom ETL/ELT scripts
-
Setting up automatic generation of ETL/ELT code
-
Transforming data into a compatible format
-
Cleaning data (defining missing values, outliers, duplication)
-
Loading datasets into a target database or data repository
-
Monitoring ETL/ELT performance
-
-
API integration
-
Choosing reputable and well-tested APIs
-
Ensuring API integration security
-
Enabling uninterrupted data flow and exchange between systems
-
Connecting multiple APIs
-
Improving existing API integrations
-
-
Real-time data integration
-
Establishing high-performance data infrastructure
-
Implementing data governance practices to validate, clean, transform, and enrich data
-
Ensuring change data capture (CDC)
-
Automating ETL/ELT processes for real-time data streaming
-
Selecting technologies for instant data stream processing
-
Enabling real-time data analytics
-
-
Cloud and on-premises data integration
-
Assessing your data integration needs
-
Setting up on-premises software and hardware components
-
Enabling data integration in the cloud environment
-
Implementing data protection mechanisms
-
Developing end-to-end data delivery pipelines
-
Setting up streamlined DevOps processes
-
-
IoT data integration
-
Enabling data collection from multiple sources and IoT devices
-
Prioritizing and filtering IoT data
-
Sampling and aggregating IoT data in a single storage system
-
Ensuring security system for data protection
-
-
Legacy system integration
-
Selecting cloud-based data integration platforms
-
Migrating data incrementally from legacy software to modern platforms
-
Employing middleware solutions to translate data formats and protocols
-
-
Data governance and compliance management
-
Assessing data for quality, risks, and relevance
-
Complying with industry, standards, regulations, and laws
-
Protecting data pipelines from collection to storage
-
Monitoring changes in data regulations to make timely updates
-
-
Post-integration support and optimization
-
Monitoring system performance and security post-integration
-
Improving data quality by identifying and correcting errors
-
Enhancing system security and scalability
-
Maintaining data analytics tools
-
Providing training materials and documentation to manage integrated data
-
-
ETL/ELT development and automation
-
Writing custom ETL/ELT scripts
-
Setting up automatic generation of ETL/ELT code
-
Transforming data into a compatible format
-
Cleaning data (defining missing values, outliers, duplication)
-
Loading datasets into a target database or data repository
-
Monitoring ETL/ELT performance
-
-
API integration
-
Choosing reputable and well-tested APIs
-
Ensuring API integration security
-
Enabling uninterrupted data flow and exchange between systems
-
Connecting multiple APIs
-
Improving existing API integrations
-
-
Real-time data integration
-
Establishing high-performance data infrastructure
-
Implementing data governance practices to validate, clean, transform, and enrich data
-
Ensuring change data capture (CDC)
-
Automating ETL/ELT processes for real-time data streaming
-
Selecting technologies for instant data stream processing
-
Enabling real-time data analytics
-
-
Cloud and on-premises data integration
-
Assessing your data integration needs
-
Setting up on-premises software and hardware components
-
Enabling data integration in the cloud environment
-
Implementing data protection mechanisms
-
Developing end-to-end data delivery pipelines
-
Setting up streamlined DevOps processes
-
-
IoT data integration
-
Enabling data collection from multiple sources and IoT devices
-
Prioritizing and filtering IoT data
-
Sampling and aggregating IoT data in a single storage system
-
Ensuring security system for data protection
-
-
Legacy system integration
-
Selecting cloud-based data integration platforms
-
Migrating data incrementally from legacy software to modern platforms
-
Employing middleware solutions to translate data formats and protocols
-
-
Data governance and compliance management
-
Assessing data for quality, risks, and relevance
-
Complying with industry, standards, regulations, and laws
-
Protecting data pipelines from collection to storage
-
Monitoring changes in data regulations to make timely updates
-
-
Post-integration support and optimization
-
Monitoring system performance and security post-integration
-
Improving data quality by identifying and correcting errors
-
Enhancing system security and scalability
-
Maintaining data analytics tools
-
Providing training materials and documentation to manage integrated data
-
Increase data delivery speed with automated data integration flow
Enrich data science and BI projects with relevant datasets to better understand your processes and customers.
Yalantis: A data integration consulting company with a proven portfolio
Data integration use cases across industries
-
Finance
-
Improved compliance reporting
-
Fraud detection
-
Personalized banking services
-
Consumer behavior monitoring
-
Transactional trends tracking
-
-
Healthcare
-
Real-time remote patient monitoring
-
Predictive analytics
-
Holistic patient treatment
-
Decreased readmissions
-
Optimized clinical trials
-
Accurate health forecasts
-
-
Supply chain
-
Supply chain performance analysis
-
Real-time order and shipment tracking
-
Delivery route optimization to reduce fuel consumption
-
Reduction in overstocked inventory and stockouts
-
Demand forecasting
-
Price optimization
-
-
Manufacturing
-
Production performance analysis
-
Predictive maintenance support
-
Waste reduction
-
Quality control inspections
-
Optimization of energy consumption
-
Data Modernisation:
Unlock your business data’s potential with a modern, cost-effective system that makes data accessible, actionable, and easy for your team to embrace.
Insights from an experienced data integration company
Instant analysis of time-critical data: Real-time data streaming use cases, examples, and benefits
7 best practices in metadata management for IT leaders and decision makers
Wearable technology in healthcare: a comprehensive integration guide for hospitals and clinics
Learn why you absolutely have to add wearable health devices into your healthcare facility EHR, and how it will benefit your patients and healthcare providers.
How does Yalantis address security concerns during data integration?
During the data integration consulting phase, we thoroughly assess your data sources and define sensitive datasets (personal health information (PHI), financial records, transactional data) that require the highest protection level. To ensure only authorized team members can access and manipulate data during integration, we anonymize and encrypt datasets and apply rigid role-based access controls. Once data integration is complete, we remove access rights from users who no longer need your data.
Additionally, Yalantis data experts and the SecOps team compose an incident response plan with backup/recovery strategies to be fully prepared to address security issues and software vulnerabilities. We can also provide extensive training materials on data security awareness and data privacy policies.
What types of systems can Yalantis integrate?
Yalantis data integration services include data integration between legacy systems, from cloud platforms to on-premises software, and between proprietary software solutions. By analyzing your existing software systems, tech stack, and IT infrastructure, we can devise a custom data integration pipeline that streamlines data exchange and facilitates data analytics.
What steps do you take to maintain data quality during data integration?
Invalid and poor-quality data can lead to ineffective business decisions and potential reputational risks. To build data integration flow on top-quality data, our data engineers:
- employ secure data integration tools that allow for regular automated data quality checks to standardize, clean, validate, and enrich data elements.
- ensure data accuracy and completeness by identifying missing values, errors, and incorrect entries.
- use incremental updates, real-time streaming, and scheduled refreshers to maintain data timeliness.
- adopt automated deduplication tools to eliminate redundant data records.
We also continuously monitor data quality metrics during and after data integration.
Can integrated systems handle growing data volumes in the future?
To future-proof integrated systems, we design scalable data integration pipelines that flexibly adjust to your growing data volumes. For instance, if you want to add extra IoT devices for your healthcare or manufacturing business, your data integration workflow will adapt to the changes. All you need to do is set up new devices and connect them to your IoT management system which will gather and import data seamlessly across the necessary enterprise systems. However, if any issues occur you can request our on-demand data integration consulting services and we’ll configure new data sources or IoT devices as well as fine-tune your data integration pipeline for higher efficiency.
How do you ensure compliance with GDPR, HIPAA, or other regulations during data integration?
We have extensive experience with diverse industry laws, regulations, and standards. For each business case, we need to match data integration needs with specific compliance requirements since regulations differ in their data management and data integration rules. For instance, GDPR requires data minimization and purpose limitations, HIPAA—breach notifications, and stringent security rules to protect PHI. After analyzing your needs and industry compliance requirements, we:
- devise a data governance framework to distribute ownership and roles accurately for collecting, sharing, and using integrated data.
- establish regular security and compliance audits to continuously monitor integrated data.
- put in action Identify and Access Management (IAM) policies (create separate IAM groups with proper access) to prevent unauthorized access and data breaches.
- enable interoperability and secure integrated business environment to prevent data silos which can lack proper data protection measures.
- integrate risk management and fraud detection policies.
6 challenges and solutions for successful enterprise data integration
Businesses have a lot of plates spinning. Numerous departments perform their daily tasks according to their rules, producing countless individual files. Managing these disparate datasets can be frustrating and even impossible without proper data integration and data management workflows. Below are typical data challenges that can obscure the real picture of your business performance and productivity.
Challenge 1: Data silos and data fragmentation
A high workload, many clients, and lots of daily operational tasks indicate business success. But what if people spend almost half of their working time looking for the right data to do their jobs? What if they don’t have time to respond on time to new clients because of too much manual and routine work? In this case, the company is losing clients and experiencing significant drops in employee productivity. The most amusing is that the board may not even realize the root causes of these issues, as they’ve become so frequent that the only solution the board sees is to hire more personnel. Such a decision leads to more expenses and doesn’t solve anything.
High workloads and perpetually busy employees have the board convinced that things are going great for the organization. However, this can be indicative of siloed and fragmented data that prevents people from organizing their time and workloads efficiently. Partnering with a data integration company to assess these inefficiencies can highlight areas for immediate improvement.
Solution: Investigating each department’s current documentation, processes, daily routines, issues, blockers, complaints, and data sources can give you many valuable insights to base your further decisions. Together with experienced data integration consultants, you can develop a roadmap for creating a unified documentation system that includes all the relevant datasets. This way, your employees can easily find and use the data they need.
Challenge 2: Low-quality data
Proprietary software with duplicated data elements or the same datasets that have different formats across several systems eats up CPU memory, breeds confusion, and prevents you from making a quick and important business decision. This is a description of poor-quality data. We can imagine your frustration if you need to deal with such data elements recurrently, make sense of them, and produce results.
Solution: Cooperate with a data integration consultant and a data engineering team to devise the right data quality management workflow. It’s critical to clean, transform, and enrich your data to guarantee its timeliness, consistency, integrity, and completeness. High-quality data is fuel for efficient data analytics. Through our data integration consulting services, Yalantis experts use the latest data integration tools for regular data quality checks and write custom code for the areas that need customization and high security.
Challenge 3: Legacy software
Outdated software systems can become a significant roadblock on the way to business growth. Such systems may have issues integrating with modern applications, handling the increasing volume of data, and supporting real-time analytics. As a result, teams waste valuable time manually inputting or reconciling information, leading to errors and inefficiencies. Plus, there is a risk of system failure without due and regular support, exposing the organization to potential downtime and data loss.
Solution: Modernizing legacy systems doesn’t mean throwing them out entirely. A trusted data integration consultancy team can assess which parts of your legacy system are still useful and integrate them with newer, more adaptable solutions. Yalantis, a leader in data integration consulting, specializes in creating modular architectures and data migration strategies that help businesses preserve functionality while embracing innovation.
Challenge 4: Lack of data governance framework
Custom data governance frameworks can prevent data inconsistencies, unauthorized access to proprietary systems, and compliance risks. Without clear governance, employees can violate organizational policies when using and storing data, resulting in data breaches, fines, and reputational damage. A lack of clear protocol for data ownership can slow down business decision-making and cause revenue losses.
Solution: Establishing a clear data governance framework starts with defining roles, responsibilities, and policies around data usage and access. Through tailored data integration services, Yalantis works with organizations to implement automated data integration tools that enforce governance rules, including access controls, audit trails, and compliance monitoring. These tools are critical components of a successful data integration service.
Challenge 5: Failing business intelligence and reporting
When BI systems produce incomplete or irrelevant reports and dashboards, decision-makers rely on guesswork rather than actionable insights. Poorly implemented analytics tools that run on fragmented data sources, or delayed data synchronization is a waste of time, effort, and money. Such inaccuracy not only affects daily operational efficiency but also hinders long-term strategic planning.
Solution: A robust BI system depends on a well-integrated and well-structured data warehouse. Engaging a data integration company allows you to build centralized and standardized data integration pipelines, feeding accurate and up-to-date information into a data warehouse and BI tools. At Yalantis, we design tailored BI and advanced analytics solutions as part of our data integration consulting services, offering real-time dashboards and automated reporting to empower businesses to act with confidence.
Challenge 6: High data infrastructure costs
Maintaining on-premises data infrastructure or inefficient cloud setups can burn through your budget. Obsolete hardware components, redundant storage, and unoptimized data integration and management workflows often result in unexpected expenses.
Solution: For instance, transitioning to a pay-as-you-go cloud-based or hybrid data infrastructure can reduce costs while improving performance. A specialized data integration consultancy company like Yalantis can evaluate your infrastructure and identify cost-saving opportunities. Our data integration as a service helps businesses adopt a scalable, optimized data integration solution that meets evolving needs while reducing expenses.
Data integration consulting services to bridge the gap between siloed enterprise data and real-time insights
If you consider integrating your enterprise data in a unified format and making it available for your employees just a click away, our data integration consultants can help you all the way through:
- researching each department’s current state
- defining relevant data sources
- analyzing your functional and non-functional requirements
- prioritizing business goals
- planning and optimizing the budget for the new data integration and management workflow
- selecting suitable tech stack and data analytics tools
Data integration consultancy is also helpful if you want to follow an incremental path toward improved data operations. Starting slow can win you a load of experience and prepare you for the challenges of scaling your data integration solution in the future.
Devise a data integration strategy
got it!
Keep an eye on your inbox. We’ll be in touch shortlyrnMeanwhile, you can explore our hottest case studies and readrnclient feedback on Clutch.
See Yalantis reviews
Lisa Panchenko
Senior Engagement Manager
Your steps with Yalantis
-
Schedule a call
-
We collect your requirements
-
We offer a solution
-
We succeed together!