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OUR CAPABILITIES

Cloud & Platform Modernization
Managed Services
Data Management
Strategic  Advisory Services
Modern Analytics
AI- Augmented RPA
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Cloud & Platform Modernization

  • Cloud Roadmap, Migration

  • Cloud native data and analytics

  • Data lake and hubs

  • Modern Data Integration

  • Data Virtualization

Digital transformation can be empowering at an organizational scale. It can help transform the customer experience, power innovation, increase agility and flexibility, reduce operating costs and drive data-based decision-making.But outdated IT infrastructures and applications too often can stand in the way. Genuine digital transformation — in which enterprises take full advantage of  digital technologies such as artificial intelligence, automation, connected devices and remote collaboration and communications platforms — benefit from a cloud modernization strategy that involves people, processes and technology.

While several types of modernization, including infrastructure modernization, platform modernization, application modernization, business process modernization and cultural/workplace modernization, can enable full digital transformation, advancements in cloud and related technologies can have a significant impact on each of them.

 

Effective digital modernization initiatives are typically coordinated efforts. It makes little sense, for example, to launch an application modernization project in isolation when its effectiveness hinges on modernized infrastructures, platforms and business processes based in the cloud.

 

We believe in a holistic approach.

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Managed Services

  • Data & Analytics COE

  • Platform administration and upgrades

  • Platform & Application support

  • DevOps

  • Upgrades & Optimization

Every day more and more businesses are jumping on the bandwagon. But what does managed services actually mean and how can you tell if an IT Support company is not just using the word as a marketing tool, but is in fact only offering “flat rate” services packaged as “managed services”?

As a definition, Managed Services allows a business to offload IT operations to a service provider, known as a Managed Services Provider. The managed service provider assumes an ongoing responsibility for 24-hour monitoring, managing and/or problem resolution for the IT systems within a business.

Managed Service models have evolved over time, and the seasoned providers have perfected their delivery. It is very effective for a business that:

•Relies on their IT Infrastructure to properly support their daily business processes

•Do not have sufficiently trained staff or time to formally deal with proper maintenance, updates and repairs

•Want to pay one monthly, flat fee for services to provide a high level of service quality to the business

For most business services, IT underpins the business engine. From software to hardware and the skills required to keep the service running, a company could invest significant capital in building and maintaining the in-house support staff. However, given the maturity of the managed service models and the shift to virtualization and cloud, the need for on-site IT staff can be limited to the exceptions where operational sensitivity justifies it. To ensure greater IT cost predictability amid uncertain requirements, a company may consider leveraging managed service experts.

MSPs usually price their services on a subscription basis. Based on the services selected, the pricing is usually scoped on the number of devices with pricing aligned to packages across a range of categories. Some provide customer support on-site when required. Basic services often start with a monitoring service, which identifies potential issues, which you resolve on your own. At the other end of the spectrum, service providers offer comprehensive managed services that cover everything from alerts through problem resolution.

 
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Data Management

Your company’s data is one of its most valuable assets. So creating data management policies, procedures, and processes to ensure it remains accurate, secure, accessible, and usable for analytics insights should be a top priority.

  • Governance

  • Architecture

  • Database Systems

  • Master Data and Metadata Management (MDM)

  • Quality Control

  • Data Integration and Definition

  • Warehousing

  • Transformation

  • Data Security

  • SAP – S4HANA

The practice of managing data as a valuable resource to unlock its potential for an organization. Managing data effectively requires having a data strategy and reliable methods to access, integrate, cleanse, govern, store and prepare data for analytics. In our digital world, data pours into organizations from many sources – operational and transactional systems, scanners, sensors, smart devices, social media, video and text. But the value of data is not based on its source, quality or format. Its value depends on what you do with it. 

Benifits of Data Management : 

Better reporting

Easier decision-making

Enhanced customer service

Increased transparency

Improved regulatory compliance

Less manual processing

Fewer errors

 
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Strategic Advisory Services

  • Visioning & Product Road Mapping

  • Architecture Consulting

  • Tech Assessments

  • Performance Optimization

  • Data & Analytics Governance

 
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Modern Analytics

  • Data Visualization

  • Enterprise BI

  • Self-service BI

  • Custom Analytics 

  • Augmented, Next-Gen, Geo-Spatial Analytics

Being able to consume and analyze data is critical to the business. The time is right to look at modernizing your platform. Computing power has increased while computing costs have decreased, which enables real-time predictive analysis. You can leverage the work that key software providers have done to integrate their suites of tools, creating a solution that is customized for your needs. In other words, if you’re prepared to modernize, now’s the time. So here are a few thoughts about what you should look for in a modern analytics platform.

 
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RPA & AI

Automate Legacy Data Consumption

Automate Processes

Process Structured and Semistructured Data

Enhance RPA  through AI Algorithms 

Data Driven ML with Decision Engines & Prescriptive Analytics

Self Calibrating models for AI Predictive Analytics