Data management
Data Management Services
Data Never Sleeps, But It Doesn’t Have To Be A Mess
Your teams are sweating the small stuff, fighting Data every day. Sales struggles with incomplete customer records, working off spreadsheets that never match the CRM. Finance wastes weeks each quarter manually stitching together reports from mismatched systems. The IT team is always busy fixing security gaps in databases they didn’t even know existed. And when audits begin, everyone rushes to find reports that should be readily available. All draining time and productivity.
We fix Data chaos by unifying, automating your data actions and making Data access secure. We start by mapping your data sources—across ERP, CRM, spreadsheets, and other silos. Then we design a centralised data layer using Snowflake to unify your organisation’s data in real time. No more reconciling reports or duplicating entries.
We integrate your tools and systems using Apache Kafka, so data flows instantly across departments—sales dashboards update with live inventory, accounting tools sync with the latest CRM records.
To keep everything secure and compliant, we use IBM Guardium for automated data classification and encryption—ensuring sensitive information is protected before auditors or attackers ever reach it.
Here’s What Good Data Does:
40%
Increase in Productivity
3X
Faster Business Decisions
100%
Audit Ready
90%
Less Data Errors
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Poorly Managed Data Cost You Millions
Those manual reports and duplicate spreadsheets aren’t just frustrating – they’re creating real financial leaks. Customer orders fall through cracks. Inventory numbers don’t match ground reality. Compliance risks get hidden between cells.
Check out our Data management services that help you fix the gaps, protect your business and help you tap into opportunities hidden in your Data.
Imagine this, someone in your finance team is likely manually reconciling reports against customer data—unaware that their spreadsheet contains outdated customer information addresses that unknowingly violate GDPR. Meanwhile, your compliance team just got an audit notice demanding proof of data access controls – a process that typically takes 3 weeks of panic. This is what happens without governance: wasted time, unnecessary risk, and decisions made on bad data.
At Codewave, we fix problems like these by deploying intelligent governance systems that work while you sleep. We use Collibra to tag sensitive customer information across every database and spreadsheet automatically. IBM Guardium locks down high-risk data, while custom dashboards give leaders one trusted source of truth.
For example, a retail business tracks sensitive customer information and protects high-risk data. Custom dashboards provide a single, reliable source of truth. When an audit request comes in, they can generate compliance reports in minutes, saving time and reducing risk.
Raw data alone won’t drive decisions—you need a structured, scalable foundation that transforms information into actionable insights. Without a clear architecture, your data becomes fragmented, slow, and unreliable.
We use Apache Kafka to build real-time data pipelines that stream transactions, customer interactions and operational metrics the moment they happen. For unified analytics, we implement Snowflake’s cloud-native platform, while AWS Glue automates the heavy lifting of data integration. The result? Your entire organization works from the same accurate, up-to-the-minute information.
Example: A fashion retailer synchronizes online and in-store inventory in real time. Customers see accurate stock levels, sales teams spot local trends instantly, and warehouses auto-replenish bestsellers. Marketing triggers personalized promotions the moment items restock—eliminating manual updates and missed sales opportunities.
When your sales team enters a new customer in Salesforce, but the shipping department can’t find them in the ERP, and marketing emails bounce because the address format differs in Mailchimp – you’re losing money to data chaos. Duplicate records, conflicting product information, and outdated supplier details create costly errors that ripple through every department.
We solve this with master data management that establishes one authoritative version of your critical business information. Using Informatica MDM and Riversand platforms, we create golden records that automatically synchronize across all your systems. Our matching algorithms identify and merge duplicates, where the same customer or entity is entered multiple times, ensuring only one correct record exists, while preserving vital relationships, and custom workflows ensure data quality keeps improving over time.
For example, a luxury watch retailer launches a new collection. The product manager updates the central system at 9 AM. By 9:05, the website displays accurate product details, store associates have real-time inventory counts, and the mobile app shows available locations for try-ons. The warehouse system automatically allocates stock, and marketing gets clean product data for campaigns.
When your systems show conflicting versions of customer details, product information, or transaction records, every department pays the price. Sales teams waste time reconciling accounts, operational teams make decisions with unreliable numbers, and leaders lose confidence in their analytics.
We eliminate these problems through precision data quality management. We use Informatica for instant validation of incoming data, catching errors before they spread.
For existing data, we apply Python with Great Expectations frameworks to intelligently cleanse and merge duplicate records, while Talend maintains ongoing synchronization across all your platforms. This end-to-end approach works whether you’re managing patient records, financial transactions, or supply chain data.
For instance, a healthcare organization can ensure accurate patient records by automatically flagging and resolving duplicate patient entries across various systems. This eliminates the risk of wrong diagnoses and ensures healthcare professionals always work with up-to-date information.
Behind every reliable dashboard and accurate report lies a well-designed data model. We build these foundational structures that define how customer, product, and transaction data relates – ensuring your CRM, ERP, and analytics tools all speak the same language.
We make this happen through a structured approach. First, we use ERwin to design the core relationships between your business data. Then Power BI transforms these models into clear visual insights. SQL Server provides the solid database foundation, while data build tool (dbt) handles ongoing data transformations to keep everything current.
For example, by linking customer data with order and inventory information, when an order is placed, inventory levels are automatically updated. This integration ensures real-time, visual reporting through dashboards that provide immediate insights, enabling informed decision-making and eliminating data discrepancies across departments.
Our Data Management Stack
| Apache Kafka | Real-time data streaming & event processing |
| Snowflake | Cloud data warehousing & scalable analytics |
| PostgreSQL | Relational database operations & transactions |
| MongoDB | Document-oriented data storage & retrieval |
| Informatica | Enterprise data quality & governance enforcement |
| Talend | ETL/ELT pipeline development & management |
| Collibra | Metadata management & data lineage tracking |
| Great Expectations | Automated data validation & anomaly detection |
| dbt | Data transformation & modeling workflows |
| Power BI | Business intelligence & interactive dashboards |
| AWS Glue | Serverless data integration & cataloging |
| Datadog | Performance monitoring & alerting |
Don't Let Bad Data Cost You Another Quarter
Industries We Serve
| Retail | Unifies customer purchase history, inventory, and sales data for real-time inventory management and personalized marketing. Improves decision-making and enhances customer experience. |
| Fintech | Ensures compliance with regulations (GDPR, CCPA), secures transaction data, and enables accurate financial reporting for risk management and fraud detection. |
| Education | Integrates student data, course performance, and alumni records for better tracking, personalized learning, and improved administrative decisions. |
| Energy | Tracks consumption patterns, optimizes resource allocation, and enhances predictive maintenance, leading to efficient energy distribution and cost savings. |
| Healthcare | Ensures accurate patient records, simplify operations, and maintains compliance with regulations, improving patient care and reducing errors. |
| Insurance | Improves risk assessment, fraud detection, and claims processing, ensuring accurate data for underwriting and enhanced regulatory compliance. |
Proven Impact: See Our Data Success Stories
Behind every successful transformation are real challenges solved. Our case studies reveal how we:
- Turned fragmented systems into seamless data flows
- Replaced uncertainty with trusted decision-making
- Built foundations for continuous innovation
We transform companies!
Codewave is an award-winning company that transforms businesses by generating ideas, building products, and accelerating growth.
Frequently asked questions
Data management services involve the collection, integration, processing, and storage of both structured and unstructured data. These services ensure the quality, availability, security, and disaster recovery of business-critical information.
The four key types of data management are Data Governance, which establishes rules and standards for data management; Data Quality Management, which ensures the accuracy and consistency of data; Data Security, which protects data from unauthorized access and breaches; and Data Warehousing, which involves the creation and management of centralized data storage.
Data management services improve decision-making, enhance operational efficiency, ensure data security, reduce risks, and help organizations comply with regulatory requirements.
The project duration depends on factors like project scope, data complexity, team size, and technology stack. Typically, the timeline is determined after understanding the project requirements and goals.
The cost is influenced by factors such as the technology used, project complexity and scope, urgency of completion, engagement model, and the current state of the data being managed.
Outsourcing to a specialized provider ensures access to experienced professionals and cutting-edge technology. It allows companies to focus on core operations while experts handle complex data tasks efficiently and securely.
We use the latest cybersecurity practices to protect data, including encryption, secure data access controls, and regular vulnerability assessments, ensuring data integrity and confidentiality.
Data integration is the process of combining data from different sources into a unified system. This helps ensure that all systems within an organization work with the same set of reliable, up-to-date data.
Data is cleansed by removing duplicates, correcting inaccuracies, and updating outdated information. Validation ensures that the data meets quality standards, and we use automated tools to perform these tasks efficiently.
Yes, we assist organizations in securely migrating data from one system to another, ensuring its integrity and smooth functioning in the new environment without data loss or corruption.
Latest thinking
Inaccurate data costs companies an average of $15 million annually.
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