Why Is Data Management Important?
Visibility
Managing data in accordance with your business strategy helps increase the transparency of data workflows, which boosts accurate decisions and leads to tangible outcomes.
Accessibility
Data management tools allow you to get well-structured and organized data storage with customized permissions so that end users can access it in a time-efficient manner.
Security
With strict requirements for information security, keeping data assets safe from breaches is of utmost importance when companies outsource the development of data management solutions.
Governance
Leverage data management to build processes and policies that add trust and align the use of digital information at the organization with the key industry regulations.
Primarily, data management services help organizations to:
- eliminate data silos
- improve data quality
- ensure regulatory compliance
- create a reliable foundation for AI, analytics, and reporting.
Today, many businesses struggle with inconsistent information, limited visibility across departments, and growing security risks. So, embracing data management services is a wise move.
Take Off with Data Management Consulting
System Audit
Before implementing any data management solution, scrutinize your current data landscape with our audit services. It will help you get a full 360° view of your environment so you know exactly where you stand and what needs to be done first.
Implementation Advisory
Successful data management initiatives help businesses not only survive tough times but, most importantly, thrive. We ensure your data project is launched on time, on budget, and on strategy, succeeding at every stage of implementation.
Modernization Strategy
Whether it’s your current infrastructure that is not ready to embrace new data solutions or you plan for future growth and innovation by leveraging data management, our team will take modernization steps relevant to your scenario.
Our Enterprise Data Management Services to Fuel Accurate Decisions
Data Governance
As a data management service provider, we help businesses define a data strategy and choose the right approach to use digital information in the most efficient way.
Data Storage
We build various solutions like data warehouses or data lakes that support different options for storing your data, whether it is on-premise, in the cloud, or a hybrid model.
Data Preparation
Our team will clean, transform, and prepare raw data so that only relevant information in the required format is taken for further processing to deliver the best results.
Data Modeling
To provide you with a structured flow of data, we’ll design a simplified diagram of your software solution with all data components and connections between them.
Data Analytics
Leverage data analytics that relies on advanced technologies to deliver valuable insights, boost decision-making, and unlock the full potential of your business.
Data Integration
We use modern API technologies and integration practices to connect all data endpoints and consolidate information from disparate sources to make your data an asset.
Data Processing
Velvetech helps companies develop software solutions to facilitate data processing, provide ground for implementing data science, and drive business intelligence.
Data Migration
If you need to migrate your data from one system or application to another, then our team is ready to help you with transforming and loading it into the target location.
Ready to go ahead with data management software development?
Why Choose Velvetech for Data Management Services?
For over 20 years, Velvetech has been trusted by global organizations as a company with extensive expertise in providing data management services. We know the value of information for modern business operations and tailor every step of the development journey to each client and their specific industry.
Data quality standards like security, accuracy, and consistency lie at the core of our approach. That’s why we deliver first-grade solutions that turn data from an operational burden to a comprehensive advantage. With the best data management practices and tech tools, any type of data can be tamed.
Data Management Systems for Any Challenges
Data Lake
Go for a scalable repository that stores structured and unstructured data in its raw form. This sets the ground for advanced analytics, AI, and real-time processing.
Data Warehouse
Want to make decisions swiftly, leverage business intelligence, or build effective reports? Then, a data warehouse with its structured storage is a good fit here.
Data Marts
If your data management strategy targets several departments, a data mart system will suit you, dividing information into focused subsets for specific business units.
Data Lakehouse
Embrace the power of a duo for modern architecture: benefit from the flexibility of a data lake and the performance and governance of a data warehouse.
Data Mesh
This is a complex, decentralized approach that will empower your domain teams to own, manage, and share data as a product across the organization.
Data Fabric
Implement a data fabric to unify distributed data, automate integration, and ensure consistent governance across hybrid and multi-cloud environments.
Typically, an effective data management strategy includes a series of necessary steps and components:
- data architecture design
- integration and pipeline development
- data quality management
- governance frameworks
- security and compliance controls
- scalable storage solutions.
It also defines standards for metadata management, access control, monitoring, and lifecycle management. However, most importantly, it aligns data processes with business objectives, which ensures that information supports analytics, operational efficiency, and future AI initiatives.
Transforming Business Operations with a BI Approach
You must be working with volumes of data daily, and we know it. It’s time to extract meaningful insights from it.
Watch our webinar to learn the secrets of business intelligence, modern BI tools for data analysis, and best practices for accurate results.
How Can Data Management Help You?
Looking for data management consulting first?
Components of Data Management
Data Pipelines
Our data engineers create automated pipelines, a set of data processing elements, to support moving data from various points.
ETLs
The ETL approach is widely used when it comes to transforming your data while moving it to a database, data warehouse, or cloud.
Data Catalogs
Track changes, locations, and quality of your data with data catalogs that help better organize your information and easily find it.
Data Architecture
We’ll design a data architecture that suits your business case and describes how your IT infrastructure will support your data strategy.
Data Warehouses
A core component of business intelligence, the data warehouse centralizes your information and paves the way for its analysis.
Data Visualization
Embrace data-driven dashboards and intuitive charts to visualize values and metrics and get meaningful insights for better decision-making.
Data Storage
As an integral part of our data management services, we’ll provide you with the right solution to store your data on-premise or in the cloud.
Data Governance
Ensure data availability, integrity, and security by setting policies that help collect, process, store, and dispose information.
The cost depends on a multitude of factors: your project scope, system complexity, how big your data is, where a partner you outsource services to is from, and whether modernization or migration is involved.
Smaller initiatives, such as system audits or advisory engagements, may start from $10K+. Enterprise-wide architecture design and implementation can range from $50K to $250K or more. Velvetech conducts a detailed assessment to define a realistic budget based on your current infrastructure and long-term goals.
Velvetech has implemented Creatio CRM, AI-based call analytics, and a speech-to-text transcription service. Our collaboration with DataGuard USA resulted in a range of solutions that helped them better store, monitor, analyze, and retrieve vital customer data.
Insurance Document Processing Automation
PPO Advisors, a top dental insurance consultant, turned to our team with a request to automate the fee schedules analysis they provide. The company relied on a manual approach to process a wide range of data. We’ve built a custom middleware solution that automated the client’s document management and report generation workflows.
RPA Solution for Customer Data Management
20/20 Foresight was looking for a solution that would help them process millions of records faster and replace manual data entry. We’ve implemented the technology stack to facilitate customer data management, from processing to cleaning, which resulted in a 20% growth of the company’s database and improved services.
Data Integration for a Dental Marketplace
Medical Data Integration and Management
with the Right Data Management Strategy
It’s true that behind every successful AI initiative lies consistent and high-quality data. When data sets are incomplete or poorly governed, they can undermine even the most advanced analytics models. That’s why we focus on providing data quality management services first and then build the foundation for your successful AI or business intelligence solution.
At Velvetech, we prepare environments for AI adoption, which has already become an integral part of many business operations. For that, our team establishes scalable architectures, reliable data pipelines, and clear governance frameworks. Afterwards, we use trusted data to deploy analytics, ML and predictive models, and real-time dashboards.
Accelerate your business decisions with AI and data management union
Our Data Management Process
Technologies We Use
In short, data management focuses on the overall strategy, governance, quality, security, and organization of data across the enterprise. Data engineering, on the other hand, concentrates on building and maintaining the technical infrastructure, such as data pipelines, processing frameworks, and storage systems.
While data management defines how data should be governed and used, data engineering builds the systems that make it possible.
What Our Clients Say
