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Data Management Services and Solutions

Driving innovation through Enterprise Data Management

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.

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Data Governance

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. 

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Data Architecture and Security

Functional data architecture with data security helps to structure and secure the operational environment in which the data will be integrated, stored and processed.

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Data Warehousing and BI

Transforming input data into a suitable format for creating reliable insights. Enabling business users with insights to make intelligent and data-driven business decisions.

Consolidate Business data with Data Management Strategy

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

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Enterprise Data Management (EDM) offerings for an agile and data-centric organization 

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Master data management (MDM)

MDM solutions are driven around reducing redundant, inconsistent data and providing a unified view of insights and information.

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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.

Enterprise Data Management Services Platforms

Manage, Transform, govern, control, improve and exploit data for beneficial business outcome.

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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.

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Azure End-to-End EDM Services

Manage Data Assets with Business Glossary, Dictionary, Data modeling, and discovery, Source connectivity, and more with Azure.

Rapid access to High-Quality and Business-ready Pipelines and Insights

Data Integration architecture solutions empower enterprises with end-to-end lifecycle management

Adapt and respond to change faster and effectively by managing enterprise data

XenonStack provides assessments, strategy and implementation for effective and flexible Enterprise Data Management .

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Key Enablers

Enablers for Accelerating Digital Transformation

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Enterprise AI

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Big Data Engineering

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Data Science

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DevOps

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Data Visualization

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Here are our Recommendations...

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Digital Transformation Enablers

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Banking and Finance Sector

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Education

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Retail

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Media

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Enablers for Accelerating Digital Transformation

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    Enterprise AI

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    Big Data Engineering

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    DevOps

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    Data Visualization

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    Cloud Native Applications

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    Kubernetes

Related Insights

Overcome the challenges posed by complex mass-scale enterprise IT

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Overcome the challenges posed by complex mass-scale enterprise IT

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Leveraging DevOps Principles for Better Analytics

Leveraging DevOps Principles for Better Analytics

Security Management and best practices

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Security Management and best practices

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Streaming Analytics

Data Catalog

Data Lineage

Data Denormalization

Streaming Analytics

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

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.

Data Denormalization

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.