Our Microsoft SQL engineers use this database management system for the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network.
This is a cloud-based data integration service that allows our engineers to create data-driven workflows in the cloud for orchestrating and automating data movement and data transformation. We shall not be able to store any data here since Azure Data Factory does not store any data itself.
AWS Lambda is a Serverless, event-driven compute service used by our engineers to run the code virtually on any type of application or backend service without provisioning or managing servers. We can trigger Lambda from over 200 AWS services and software-as-a-service (SaaS) applications and only pay for what you use.
With Power Apps, our engineers can customise, and develop your websites & apps using drag-and-drop technology and built-in templates. By being a part of your digital transformation journey, our Power Apps experts can guide you from use case analysis to maintenance and support.
As a part of Microsoft Azure cloud service, we use Microsoft Graph Service and Microsoft Graph API . This can run on any Microsoft cloud platform such as Azure, on-premise systems or Google Cloud Platform. To connect to Microsoft Maps, launching it on Azure cloud is the easiest way.
Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes using AWS-designed hardware and machine learning to deliver the best price-performance at any scale.
Databricks runs on AWS and integrates with all of the major services you use like S3, EC2, Redshift and more. The Databricks Lakehouse Platform sits at the heart of the AWS ecosystem and easily integrates with popular Data + AI services like Kinesis streams, S3 buckets, Glue, Athena, Redshift, QuickSight and much more.
Snowflake offers a cloud-based data storage and analytics service, generally termed “data-as-a-service”. It allows corporate users to store and analyze data using cloud-based hardware and software. It offers unified data across clouds to accelerate and scale analytics with near-zero administration.
Data Visualisation Platform for Enterprises
Data Analysis for FinTech Industry
Data Automation for Marketplace Industry
ML for Retail Demand Forecasting
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Trusted and Proven Engagement Model
- A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
- Our NDA-driven process is established to keep clients’ data and IP safe and secure.
- The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
- This helps clarify the goals, and limitations, and deliver quality products & services.
- Our engagement model defines the project size, project development plan, duration, concept, POC etc.
- Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
- The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
- On signing the SOW, an official project kick-off meeting shall be initiated.
- Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.