Data & Advanced Analytics

Harness the power of data by combining and harmonizing it from different sources leveraging state of the art services available on Cloud.

Insights: To drive business success by leveraging modern BI tools.

Integration: To support business needs for real-time data insights and intelligence.

Intelligence: To provide predictive and prescriptive recommendations on the company’s ecosystem & public data.

Click on the service for additional information

Intelligence: Data and insights taken to the next level of agile and responsive business processes by developing generative AI and machine learning models to provide predictive and prescriptive recommendations on the company’s private ecosystem and public data.

Insights: Exploratory data analysis to determine relevance for business processes and develop actionable operational models and insights to drive business success leveraging modern BI tools.

Integration: The right data fabric architecture and design to build high-fidelity data pipelines covering all scenarios of real-time, batch, streaming and event-based source and sinks, to support the ever-growing business need for real-time data insights and intelligence.

We cover all aspects of generative AI, from establishing a data foundation and identifying the use cases, to incorporating LLMOps. Our Implementation philosophy is based on the responsible and effective use of generative AI. We specialize in following GenAI services:

  1. Creating Chatbots and Virtual Assistant
    • We build enterprise grade chat-bots and virtual assistants to support business needs
    • Flexible architecture to adapt to the changing technology.
  2. Implement LLM (single/multimodal) centric use cases that may require:
    • Identifying LLMs / SLMs as per the use case.
    • Tune LLM to your DATA (Prompt Engineering /Fine Tuning) 
    • RAG implementation
  1. Enhancing established products with AI
    • This service includes assessment of already existing products and possibility of AI enhancements to it.
    • We help prioritizing the use case and co-work with your development team to enhance product features enabled by AI
  2. Build and Improve Recommendation Systems for your business needs.
  3. Setup Intelligent Document Processing System
  4. Anomaly Detection
  5. Image and Video Processing
  1. We help businesses to adapt  standardized processes from ad hoc ML development.
  2. Help business to move from Experimentation to productionizable ML.
  1. We help businesses to set up their own AI practice from scratch. We support:
    • Recruitment 
    • Setting up Infrastructure that caters to your long term AI vision.
    • Identifying the use cases  that are of relevance to your business. 
    • Translate the first few use cases to ML problems and support to solve and bring business value.
  2. Handover to the business
  3. Mentoring and support

Our AI powered Database Migration Services can help you migrate databases to Google cloud with minimal downtime and confidence saving up to 50% of your efforts.We leverage AI based migration assessment powered by Google cloud DMA and Generative AI based schema translation and business logic conversion to accelerate your migrations

We currently support following heterogeneous migrations, contact us to know more.

The Data-Driven Insight platform is built on a Modular Data Platform that addresses critical challenges such as integration (with an agile framework), processing (config-driven), and the semantic layer (consumption-driven).

Our implementations include:

  • Enterprise BI Platform: Serving the diverse needs of the enterprise, from sales and finance to people and organizational functions.
  • Platform Migration: Transitioning from existing on-premises or cloud-hosted environments to new platforms. These migrations are driven by assessments to identify pain points in the historical setup and address them in the new platform.

We focus on developing platforms that cater to different decision-making levels:

  • Operational Level: BI layer for executives to streamline operations.
  • Tactical Level: BI layer to assist mid-level leadership in making tactical decisions.
  • Strategic Level: BI layer to support leadership in shaping long-term strategies.

Tools: Power BI, Tableau, Looker, QuickSight, MicroStrategy, and more.

Explore and analyze your data to summarize its key characteristics. This process aids in understanding the data’s structure, identifying trends, and detecting anomalies. Start by understanding the variables, checking for missing values, and identifying data types.

Next, summarize the data using descriptive and distribution statistics. Visualize patterns, pinpoint anomalies, and identify correlations within the data.

Incorporate analytics at various levels:

  • Descriptive Analytics: Understand what happened.
  • Diagnostic Analytics: Determine why it happened.
  • Predictive Analytics: Anticipate what is likely to happen.
  • Prescriptive Analytics: Identify the best course of action to achieve desired outcomes.

Tools: Google BigQuery, Amazon QuickSight, Azure Synapse Analytics, Snowflake, Databricks, AWS Redshift etc.

  1. Lakehouse– Empower businesses to uncover valuable insights and drive innovation by storing and processing structured and unstructured data
  2. Realtime Data– Enable organizations to make informed decisions, optimize operations, and deliver personalized experiences by implementing solutions on Apache Kafka, GCP Pub/Sub, AWS Kinesis and Azure Event Hubs
  3. ETL/ELT– Consolidate data from multiple sources ensuring data quality and optimization for analysis with Informatica, Azure Databricks, Cloud Data Fusion, Talend, AWS Glue, DBT and Dataform
  4. IoT– Create a connected, efficient and intelligent world leading to increased efficiency, cost reduction and enhanced customer experience
  1. Data Governance– Establish data governance policies and procedures to effectively manage data accessibility, data ownership, data deletion and data security with Collibra, OpenMetadata, Dataplex
  2. Metadata Management- Strategize and implement metadata management practices to reduce data search time, enhance collaboration among teams and comply with data regulations
  3. Data security and Compliance – Ensure that data is protected from unauthorized access, disclosure, disruption, modification or destruction, while adhering to relevant industry regulations HIPAA, CCPA, GDPR
  4. Data Validation and Quality Assurance– Enable robust data validation and quality assurance practices to enhance the value of the data and build trust in data-driven decisions
  1. Orchestration– Ensure efficient, accurate and timely processing of data pipelines via optimized implementation of Apache Airflow, Cloud Composer, Managed Workflows for Apache Airflow(MWAA), Azure Data Factory and Control-M
  2. Automated Deployment– Accelerate your data pipeline delivery with automated Continuous Integration and Continuous Deployment (CI/CD) pipelines using tools like Jenkins, Cloud Build, GitLab, Azure DevOps and AWS Code Build & Deploy
  1. Data Warehouses– Transform raw data (SQL & NoSQL) into actionable insights to drive business growth and success across Google Cloud Platform, AWS and Azure
  2. Data Modeling– Develop enterprise grade data models to reap significant benefits in terms of data quality, efficiency, and decision-making
    • 3NF for OLTP systems
    • Dimensional Modeling for OLAP systems
    • Data Vault for OLAP systems

Integration: The right data fabric architecture and design to build high-fidelity data pipelines covering all scenarios of real-time, batch, streaming and event-based source and sinks, to support the ever-growing business need for real-time data insights and intelligence.

Intelligence:

Data and insights taken to the next level of agile and responsive business processes by developing generative AI and machine learning models to provide predictive and prescriptive recommendations on the company’s private ecosystem and public data.

We cover all aspects of generative AI, from establishing a data foundation and identifying the use cases, to incorporating LLMOps. Our Implementation philosophy is based on the responsible and effective use of generative AI. We specialize in following GenAI services:

  1. Creating Chatbots and Virtual Assistant
    • We build enterprise grade chat-bots and virtual assistants to support business needs
    • Flexible architecture to adapt to the changing technology.
  2. Implement LLM (single/multimodal) centric use cases that may require:
    • Identifying LLMs / SLMs as per the use case.
    • Tune LLM to your DATA (Prompt Engineering /Fine Tuning) 
    • RAG implementation
  1. Enhancing established products with AI
    • This service includes assessment of already existing products and possibility of AI enhancements to it.
    • We help prioritizing the use case and co-work with your development team to enhance product features enabled by AI
  2. Build and Improve Recommendation Systems for your business needs.
  3. Setup Intelligent Document Processing System
  4. Anomaly Detection
  5. Image and Video Processing
  1. We help businesses to adapt  standardized processes from ad hoc ML development.
  2. Help business to move from Experimentation to productionizable ML.
  1. We help businesses to set up their own AI practice from scratch. We support:
    • Recruitment 
    • Setting up Infrastructure that caters to your long term AI vision.
    • Identifying the use cases  that are of relevance to your business. 
    • Translate the first few use cases to ML problems and support to solve and bring business value.
  2. Handover to the business
  3. Mentoring and support

Insights:

Exploratory data analysis to determine relevance for business processes and develop actionable operational models and insights to drive business success leveraging modern BI tools.

Our AI powered Database Migration Services can help you migrate databases to Google cloud with minimal downtime and confidence saving up to 50% of your efforts.We leverage AI based migration assessment powered by Google cloud DMA and Generative AI based schema translation and business logic conversion to accelerate your migrations

We currently support following heterogeneous migrations, contact us to know more.

The Data-Driven Insight platform is built on a Modular Data Platform that addresses critical challenges such as integration (with an agile framework), processing (config-driven), and the semantic layer (consumption-driven).

Our implementations include:

  • Enterprise BI Platform: Serving the diverse needs of the enterprise, from sales and finance to people and organizational functions.
  • Platform Migration: Transitioning from existing on-premises or cloud-hosted environments to new platforms. These migrations are driven by assessments to identify pain points in the historical setup and address them in the new platform.

We focus on developing platforms that cater to different decision-making levels:

  • Operational Level: BI layer for executives to streamline operations.
  • Tactical Level: BI layer to assist mid-level leadership in making tactical decisions.
  • Strategic Level: BI layer to support leadership in shaping long-term strategies.

Tools: Power BI, Tableau, Looker, QuickSight, MicroStrategy, and more.

Explore and analyze your data to summarize its key characteristics. This process aids in understanding the data’s structure, identifying trends, and detecting anomalies. Start by understanding the variables, checking for missing values, and identifying data types.

Next, summarize the data using descriptive and distribution statistics. Visualize patterns, pinpoint anomalies, and identify correlations within the data.

Incorporate analytics at various levels:

  • Descriptive Analytics: Understand what happened.
  • Diagnostic Analytics: Determine why it happened.
  • Predictive Analytics: Anticipate what is likely to happen.
  • Prescriptive Analytics: Identify the best course of action to achieve desired outcomes.

Tools: Google BigQuery, Amazon QuickSight, Azure Synapse Analytics, Snowflake, Databricks, AWS Redshift etc.

Integration:

The right data fabric architecture and design to build high-fidelity data pipelines covering all scenarios of real-time, batch, streaming and event-based source and sinks, to support the ever-growing business need for real-time data insights and intelligence.

  1. Lakehouse– Empower businesses to uncover valuable insights and drive innovation by storing and processing structured and unstructured data
  2. Realtime Data– Enable organizations to make informed decisions, optimize operations, and deliver personalized experiences by implementing solutions on Apache Kafka, GCP Pub/Sub, AWS Kinesis and Azure Event Hubs
  3. ETL/ELT– Consolidate data from multiple sources ensuring data quality and optimization for analysis with Informatica, Azure Databricks, Cloud Data Fusion, Talend, AWS Glue, DBT and Dataform
  4. IoT– Create a connected, efficient and intelligent world leading to increased efficiency, cost reduction and enhanced customer experience
  1. Data Governance– Establish data governance policies and procedures to effectively manage data accessibility, data ownership, data deletion and data security with Collibra, OpenMetadata, Dataplex
  2. Metadata Management- Strategize and implement metadata management practices to reduce data search time, enhance collaboration among teams and comply with data regulations
  3. Data security and Compliance – Ensure that data is protected from unauthorized access, disclosure, disruption, modification or destruction, while adhering to relevant industry regulations HIPAA, CCPA, GDPR
  4. Data Validation and Quality Assurance– Enable robust data validation and quality assurance practices to enhance the value of the data and build trust in data-driven decisions
  1. Orchestration– Ensure efficient, accurate and timely processing of data pipelines via optimized implementation of Apache Airflow, Cloud Composer, Managed Workflows for Apache Airflow(MWAA), Azure Data Factory and Control-M
  2. Automated Deployment– Accelerate your data pipeline delivery with automated Continuous Integration and Continuous Deployment (CI/CD) pipelines using tools like Jenkins, Cloud Build, GitLab, Azure DevOps and AWS Code Build & Deploy
  1. Data Warehouses– Transform raw data (SQL & NoSQL) into actionable insights to drive business growth and success across Google Cloud Platform, AWS and Azure
  2. Data Modeling– Develop enterprise grade data models to reap significant benefits in terms of data quality, efficiency, and decision-making
    • 3NF for OLTP systems
    • Dimensional Modeling for OLAP systems
    • Data Vault for OLAP systems

Why CLOUDSUFI?

1

Expertise-Driven Leadership

The CEO’s handpicked team, built on 15+ years of professional relationships, boasts an average tenure of 5+ years at CLOUDSUFI, and average of 20+ years of industry experience, with expertise from tech giants like Microsoft, SAP, KPMG, GE, and Bank of America.

2

Innovation Powerhouse

CLOUDSUFI’s Gen AI Lab, hiring 500 experts, redefines data processing and automates supply chains, driving cutting-edge AI innovation.

3

Grit Over Pedigree

The CLOUDSUFI team embodies resilience and determination, prioritizing grit over pedigree, driving innovation through perseverance, problem-solving, and boldness over credentials.

4

Accelerate Impact

CLOUDSUFI’s proprietary solutions, like the anti-fragility index and Velocity Packs, boost efficiency, accelerate market speed, and drive transformation.

5

Revitalizing Wisdom

Through the CLOUDSUFI Foundation, the company is committed to driving social impact by helping older generations discover their ikigai—reigniting purpose and reintegrating them into the workforce.

Accelerate Your Success and Surpass Your Potential

CPG & Manufacturing

Tackle cost pressures, increasing demand, and evolving consumer behaviors, by prioritizing sustainable supply chain management and digital manufacturing solutions for optimal results.

Digital Natives

Improve service levels, optimize operational costs and provide multicloud services on Google Cloud.

Energy

Tackle cost pressure with competitive global demand by prioritizing sustainable supply chain with digital energy production and distribution solutions.

Retail

Ensure your customers have the right products, at the right place, at the right time, and at the right price with omnichannel customer experience.

Advanced Analytics & Gen AI

Leveraging generative AI, we can create highly customized digital assistants that cater to specific roles, industries, or even individual users. It goes beyond general-purpose AI by incorporating specific domain knowledge, skills, and language patterns associated with the target persona.

Application Modernization

Reduce high application maintenance costs and technical debt, having limited agility and scalability with outdated infrastructure.

Data Warehouse Modernization

Leverage next generation data warehouses and data lakes to create enterprise data products and datamesh.

Database Migration

Lower TCO of your databases by minimizing downtime during the migration to avoid business disruptions.

Integration

We provide broad spectrum of integration solutions that facilitate seamless data exchange and process orchestration between disparate systems, applications, and platforms. They are essential for modern organizations seeking to optimize operations, enhance customer experiences, and drive innovation.

Customer Success Stories

Insights

Unleashing Business Potential Through Data Engineering and Analytics

The Data Revolution in Modern Business Data has emerged as the new...

Smooth Data Migration: Avoiding Pitfalls and Ensuring Success

In today’s rapidly evolving digital landscape, businesses continually upgrade their systems to...

The Rise of Generative AI: Innovations Across Key Industries

Generative AI is no longer confined to the realm of science fiction—it’s...

7 Signs Your Enterprise Needs Application Modernization

Remember the days of flip phones and dial-up internet? Now, imagine running...

Testimonials

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