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EDM implementation services assist organizations in managing and handling many types of data and formats, from legacy data to the most recent forms of internal and external sources. Build an effective enterprise data management transformation strategy that reduces modern architecture's complexity and automates operations by providing easy access to business users.
The main Fundamental purpose is to define policies, procedures, roles, tasks and ownership in the whole organisation. Defining the key business metrics for data consistency, quality, and trustworthiness.
Functional data architecture with data security helps to structure and secure the operational environment in which the data will be integrated, stored and processed.
Transforming input data into a suitable format for creating reliable insights. Enabling business users with insights to make intelligent and data-driven business decisions.
Every enterprise has to define the data strategy based on its needs and business objectives. Ensuring the Data reliability and lineage to produce precise insights
MDM solutions are driven around reducing redundant, inconsistent data and providing a unified view of insights and information.
Data Management Strategy
AI-driven automated discovery, classification, and metadata management solutions for businesses.
Real-Time Ingestion and Processing has driven capabilities to reduce downtime and latency, and gain visibility into the infrastructure health.
Create governance and security models for stewards to build a single source of truth to keep the organization agile.
Empowering AI and Intelligence-driven businesses. End-to-End BI Implementation and Consulting Solutions to facilitate data-driven decision-making.
Manage, Transform, govern, control, improve and exploit data for beneficial business outcome.
Google Cloud's Database Solution
Deliver the best experience to customers with Reliable, global scale, and open standards GCP solutions.
AWS Analytics Services
Reinvent business with data from its movement, storage, creation of modern architecture, analytics, log and streaming analytics, BI, and ML; AWS offers all services.
Azure End-to-End EDM Services
Manage Data Assets with Business Glossary, Dictionary, Data modeling, and discovery, Source connectivity, and more with Azure.
Data Integration architecture solutions empower enterprises with end-to-end lifecycle management
Enterprise Technology
Banking and Finance Sector
Healthcare
Education
Transportation
Retail
Enterprise AI
Big Data Engineering
XAI
DevOps
Data Science
Agentic AI Systems
RESET
Enterprises today rely on vast, rapidly evolving datasets to drive decision-making, automation, and innovation. Yet as data becomes more distributed across cloud, on-prem, and edge environments,...
What is WebAssembly? WebAssembly is a project started by the World Wide Web Consortium (W3C) in 2015 to provide a standard high-performance and machine-independent byte code that is also safe. Wasm,...
Synthetic Data Generation with Agentic AI is redefining how enterprises create, manage, and scale data pipelines. Traditional data collection methods are costly, time-consuming, and often limited by...
Data has become the cornerstone of modern enterprises, with real-time analytics shaping critical business decisions across industries. The exponential growth of data generated from various sources,...
Real-time visibility into infrastructure and application failures is essential for ensuring high availability in today’s digital environment. Traditional monitoring solutions often struggle to detect...
With the current technological developments, it is common for organizations to have access to tons of information from different angles. The structures might include structured databases,...
In the rapidly evolving environment of artificial intelligence, maybe the most exciting development is that of multi-modal agents. Next-generation AI agents can process and integrate different kinds...
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AI Agents are revolutionising industries in today’s fast-evolving world by driving rapid advancements in software development andDevOps. While traditional approaches focused heavily on innovation...
DevOps for Databases -The Beginning Traditionally, changes to a database begin with the developers building the changes they will use to write the files in an SQL format. The changes made are then...
Overview of Persistent Storage Persistent Storage is critical for running stateful containers. Kubernetes is an open-source system for automating the deployment and management of containerized...
Introduction to Intelligent Automation Intelligent Automation is one of the most recent trends in the broad field of Technology. It is also called Hyper Automation or Cognitive Automation. It is much...
Evolution of Analytics in the last decade Around ten years ago, the tools for analytics or the available resources were Excel, SQL databases, and similar relatively simple ones compared to the...
Federated Learning Overview Federated learning is a Machine Learning technique that involves training an algorithm through several decentralized edge devices or servers that carry local data samples...
Modern enterprises receive thousands of customer orders daily through multiple channels, including email, attachments, and structured documents. Processing these orders manually often results in slow...
In today’s data-driven world, enterprises are overwhelmed by the sheer volume, complexity, and compliance demands of data management. Traditional methods are no longer sufficient to ensure seamless...
Modern enterprises are rapidly shifting from isolated automation scripts to agentic, autonomous workflows powered by coordinated AI agents. As organisations scale AI adoption across data, operations,...
Human Resources (HR) professionals are constantly adapting to an ever-changing business landscape. To stay ahead in this competitive field, attending the top conferences in human resources 2025 can...
As the world of computer vision continues to evolve at lightning speed, 2026 is shaping up to be an exciting year for professionals, researchers, and students alike. Attending conferences is a...
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Introduction to Streaming Data Visualization Streaming Data Visualization gives users Real-Time Data Analytics to see the trends and patterns in the data to take action rapidly. It is the control of...
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What is user Experience Testing? User experience testing is having actual people engage with a website, app, or other product you've created and analyzing their behaviours and reactions. It is a...
Cloud computing has become a fundamental requirement for businesses navigating digital transformation in 2025. It is no longer a competitive advantage—it’s a strategic imperative for organizations...
Introduction The transition to 5G is not just a small step forward; it's a groundbreaking move that revolutionizes the entire spectrum of wireless communication. While much has been said about public...
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In supercomputing, the distribution of network traffic has an overwhelming impact on a system's overall effectiveness and reliability. With increasing application usage, more traffic has to be dealt...
In today's fast-paced digital world, large-scale application management is important. As companies more readily embrace microservices frameworks, the dilemma of deployment, scaling, and maintenance...
Introduction SLO-Based Multi-Stage Delivery The software development industry is very dynamic, and there is always a demand for delivering quality applications. Developed software is required to be...
Find out more about levaraging the true potential of AI
Streaming Analytics
Data Catalog
Data Lineage
Data Denormalization
Streaming analytics is continuously processing and analyzing data records rather than in batches. Streaming analytics is helpful for data sources that send data in small sizes in a steady flow as the data is generated.
Data Catalog provides a single self-service environment to the users, helping them find, understand, and trust the data source.
Data lineage is the process of understanding, documenting, and visualizing the data from its origin to its consumption.
Denormalization is a technique in which we add the duplicate data to one or more table. With the help of this, we can avoid costly joins in a relational database.
AI continuously monitors systems for risks before they escalate. It correlates signals across logs, metrics, and traces. This ensures faster detection, fewer incidents, and stronger reliability
Proactive detection of performance and availability issues
Root-cause analysis across microservices and environments
Automated remediation playbooks to reduce MTTR
AI converts camera feeds into instant situational awareness. It detects unusual motion and unsafe behavior in real time. Long hours of video become searchable and summarized instantly
Real-time detection of suspicious motion or intrusion
Natural language video search and instant playback
Smart summaries for audits, investigations, and compliance
Your data stack becomes intelligent and conversational. Agents surface insights, detect anomalies, and explain trends. Move from dashboards to autonomous, always-on analytics
Connects to warehouses, lakes, and streaming sources
Question-answering in natural language
Continuous monitoring for anomalies and KPI deviations
Agents identify recurring failures and performance issues. They trigger workflows that resolve common problems automatically. Your infrastructure evolves into a self-healing environment
Automated diagnostics for recurring errors
Playbook execution: restart services, scale pods, clear queues
Feedback loop for improving remediation strategies
AI continuously checks controls and compliance posture. It detects misconfigurations and risks before they escalate. Evidence collection becomes automatic and audit-ready
Continuous control checks across infrastructure and SaaS
Automated evidence collection for audits
Risk scoring and prioritized remediation recommendations
Financial and procurement workflows become proactive and insight-driven. Agents monitor spend, vendors, and contracts in real time. Approvals and sourcing decisions become faster and smarter
Real-time visibility into spend and commitments
Anomaly detection on invoices and vendor performance
Intelligent workflows for approvals and sourcing decisions
