Valutics adapts scaled agile methodologies in implementing large scale ML, Data, and BI programs. In an era where time to market is critical in providing business value, Valutics’ approach is to not only to implement cutting-edge technology solutions but to ensure that these solutions are tailored to the specific needs of the client, are driving real business value, and are implemented in an iterative agile way.

Data Strategy, Architecture, Engineering, DataOps:Valutics’ data services go beyond traditional data management. We build robust data architectures that support large-scale big data integration, real-time processing, and advanced analytics. By employing a mix of enterprise and open-source tools, we help organizations create data ecosystems that are both powerful and cost-effective.

Machine Learning:Valutics excels in developing and deploying ML models that are not only accurate but also explainable and ethical. Our approach to ML involves a thorough understanding of the client’s business needs, followed by the development of customized models that drive efficiency, predict outcomes, and uncover new opportunities. We ensure that ML models are seamlessly integrated into existing systems, providing continuous value through feedback loops and iterative improvements.

Business Intelligence:Valutics’ BI services are designed to transform data into actionable insights. We implement state-of-the-art BI platforms that allow for real-time data visualization, predictive analytics, and automated reporting. With the addition of Generative AI, our BI solutions can now provide even deeper insights, identifying trends and patterns that might otherwise go unnoticed, and enabling more proactive decision-making.

Key Differentiators:

Integrated Technology Solutions:Valutics offers a seamless blend of data management, machine learning, and business intelligence services, ensuring that all technological initiatives are aligned with business goals and the speed to value realization is the driving force.

Advanced Analytics & AI:By incorporating AI and advanced analytics into every aspect of technology consulting, Valutics helps clients stay ahead of the curve, turning data into a strategic asset.

Customization & Flexibility:Our solutions are not one-size-fits-all. Valutics tailors each service to the unique needs of the client, ensuring that technology investments deliver maximum ROI.

Ethical & Explainable AI:Valutics’ is committed to responsible AI practices, ensuring that ML models are transparent, ethical, and aligned with the client’s values and regulatory requirements.

Machine Learning / Deep Learning

Data Exploration:Analyze datasets to identify relevant features and patterns.

Data Profiling:Assess the quality, distribution, and completeness of data

Feature Engineering:Design and create features that enhance model performance

Model Training & Evaluation:Train models and evaluate performance against business objectives.

Model Approval:Establish criteria for model approval and decision-making

Model Approval:Establish criteria for model approval and decision-making

Model Deployment:Deploy models into production environments.

Model Orchestration:Manage and automate the deployment and monitoring of models.

Decision Rules & Optimization:Implement decision rules and optimization techniques for model outputs.

Model Versioning:Track and manage different versions of models.

Feedback & Updates:Implement feedback loops for continuous model improvement.

Model Governance:Establish governance frameworks for model management and compliance

Data

Data Strategy:Develop a comprehensive data strategy aligned with business goals.

Data Roadmap:Create a roadmap for data initiatives and investments.

Data Architecture:Design scalable and flexible data architectures.

Data Engineering:Build and manage data pipelines and infrastructure

Data Catalog:Implement a data catalog for metadata management and discovery.

Data Catalog:Implement a data catalog for metadata management and discovery.

DataOps:Apply DataOps practices for agile and efficient data management.

Data Implementation:Execute data projects from planning to production.

Data Testing:Conduct rigorous testing of data systems and processes.

Data Quality:Ensure high data quality through validation and monitoring

Data Governance:Implement governance frameworks to ensure data integrity and compliance

Data Security:Protect data assets with robust security measures.

Cloud

Cloud Strategy:Develop a strategy for hybrid, single, or multi-cloud environments.

Cloud Roadmap:Plan the journey to the cloud with a detailed roadmap.

Cloud Architecture:Design cloud architectures that are scalable, secure, and resilient.

Cloud Engineering:Build and manage cloud environments and infrastructure

CI/CD:Implement continuous integration and continuous deployment pipelines for cloud applications.

Cloud Implementation:Deploy and migrate applications to the cloud

Cloud Testing:Perform testing to ensure cloud systems meet performance and reliability standards.

Cloud Governance:Establish governance frameworks for cloud management and compliance

Cloud Security:Implement security measures to protect cloud assets.

Cloud Production Support:Provide ongoing support for cloud environments in production.

Cloud Cost Reduction:Optimize efficient utilization of cloud resources through Valutics frameworks & accelerators.

Business Intelligence Services

BI Strategy & Roadmap:Strategic Planning, BI Architecture Design

Data Visualization:Dashboards, Reporting, Data Storytelling

Data Lakes:Data Integration, ETL, Data Lakes

Data Analysis:Descriptive Analytics, Predictive Analytics, Prescriptive Analytics

Performance Management:KPI Tracking, Balanced Scorecards, Financial Planning & Analysis

Self-Service Analytics:Provide Ad-hoc BI Reporting capabilities to End Users for customized Dashboards

Data Quality Management:Master Data Management (MDM), Data Lineage, Provenance

Infrastructure Services

Infrastructure Strategy:Develop strategies for on-premises, cloud, and hybrid infrastructures.

Network Management:Design, implement, and manage secure and efficient networks.

Server Management:Provide management and maintenance of physical and virtual servers.

Storage Solutions:Design and implement scalable and secure storage solutions.

Data Center Management:Manage and optimize data center operations.

Virtualization:Implement and manage virtualized environments to optimize resources

Disaster Recovery:Develop and implement disaster recovery plans to ensure business continuity.

Infrastructure Security:Implement security measures to protect infrastructure assets.

Monitoring & Optimization:Continuously monitor and optimize infrastructure performance

Infrastructure Automation:Automate infrastructure management processes for efficiency.

End-User Support:Provide support for end-user devices, applications, and services.

Vendor Management:Manage relationships with infrastructure vendors and service providers.

Tools & Technologies that we have evaluated/implemented:

Cloud Platforms:AWS, Azure, Google Cloud (GCP), IBM Cloud, Oracle Cloud

Technologies & Tools:All leading Enterprise and Open-Source Tools including:

Generative AI

Enterprise:OpenAI GPT, Google Cloud AI, IBM Watson, Microsoft Azure OpenAI, NVIDIA NeMo

Open Source:Hugging Face, GPT-Neo, DeepSpeed, EleutherAI, BigGAN

Machine Learning (ML) & Deep Learning

Enterprise:Google AI Platform, AWS SageMaker, IBM Watson Studio, Microsoft Azure ML

Open Source:TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, H2O.ai

Business Intelligence (BI)

Enterprise:Tableau, Power BI, Looker, QlikView, SAP BusinessObjects

Open Source:Apache Superset, Metabase, Redash, Grafana, BIRT

Data Engineering

Enterprise:Talend, Informatica, Alteryx, IBM DataStage, AWS Glue, FiveTran, StreamSets

Open Source:Apache Spark, Apache Kafka, Apache Nifi, dbt (data build tool), Apache Airflow

Data Pipelines

Enterprise:Informatica, Matillion, Azure Data Factory, Google Dataflow, AWS Data Pipeline

Open Source:Apache Beam, Apache Airflow, Luigi, Prefect, Dagster

Data Catalog

Enterprise:Collibra, Informatica, Alation, Microsoft Purview, IBM Watson Knowledge Catalog

Open Source:Amundsen, DataHub, Apache Atlas, LinkedIn DataHub, Marquez

Data Governance

Enterprise:Collibra, Informatica Axon, IBM InfoSphere, SAP Master Data Governance, Talend Data Governance

Open Source:Apache Atlas, OpenMetadata, Amundsen, LinkedIn DataHub, Magda

Master Data Management (MDM)

Enterprise:Informatica MDM, IBM InfoSphere MDM, Oracle MDM, SAP Master Data Governance

Open Source:Pimcore, OpenMDM, Apache Atlas (with extensions), Talend Open Studio

Data Modeling

Enterprise:eRWin, Lucidchart, Toad, ER/Studio, IBM InfoSphere, MySQL Workbench

Open Source:ERDLab.io, Draw.io, Dbdiagram.io, Archi

Data Quality

Enterprise:Informatica Data Quality, Talend Data Quality, IBM InfoSphere Information Analyzer, Oracle Enterprise Data Quality

Open Source:Great Expectations, Deequ, PyDeequ, OpenRefine, Talend Open Studio

Automated Data and ML Testing

Enterprise:Tricentis, DataRobot, Informatica Test Data Management, Validata

Open Source:Great Expectations, Soda SQL, pytest, Deepchecks, H2O.ai

Python Frameworks

Enterprise:None (Python frameworks are predominantly open source)

Open Source:Flask, Django, FastAPI, TensorFlow, PyTorch

Scala Frameworks

Enterprise:None (Scala frameworks are predominantly open source)

Open Source:Akka, Play Framework, Scalatra, Apache Spark, Kafka Streams

Spring Framework

Enterprise:VMware Tanzu (enterprise support for Spring)

Open Source:Spring Boot, Spring Cloud, Spring Data, Spring Security, Spring Batch

DataOps

Enterprise:IBM Cloud Pak for Data, Informatica DataOps, TIBCO DataOps, DataKitchen

Open Source:Apache NiFi, DataOps.live, Prefect, Dagster, Metaflow

MLOps

Enterprise:Azure ML, AWS SageMaker, Google AI Platform, IBM Watson Studio

Open Source:MLflow, Kubeflow, TFX (TensorFlow Extended), Seldon, BentoML

CI/CD

Enterprise:GitLab, CircleCI, Jenkins X, Azure DevOps, AWS CodePipeline

Open Source:Jenkins, GitHub Actions, Travis CI, GoCD, Tekton

DevOps

Enterprise:Red Hat OpenShift, HashiCorp Terraform Enterprise, Puppet Enterprise, Chef Infra

Open Source:Docker, Kubernetes, Ansible, Terraform, Prometheus

Data & Enterprise Security

Enterprise:Palo Alto Networks, Cisco Secure, IBM Guardium, Splunk, CyberArk

Open Source:HashiCorp Vault, Open Policy Agent (OPA), Falco, Suricata, OSSEC

Other Critical Components

Enterprise:VMware Tanzu, Red Hat OpenShift, Confluent Kafka, SAP HANA, Microsoft Dynamics

Open Source:Apache Kafka, Elasticsearch, Redis, PostgreSQL, MongoDB