Data and analytics services

Transform raw numbers into actionable insights with the best of AWS's analytics capabilities, to drive growth, efficiency, and innovation.

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AWS Data analytics
AWS ML
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What we do

We specialize in transforming your data into a strategic asset, leveraging the power of AWS to offer comprehensive data analytics solutions.

Data Management

Automate the tasks required to set up a data lake, significantly saving time in defining data structures, schema, and transformations, ensuring your data is accessible, scalable and organized.

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Advanced Analytics

Gain insights faster from all your data with interactive analysis, big data processing, data warehousing, real-time analytics, operational analytics, dashboards, visualizations and more.

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Predictive Analytics

Create, train, and deploy ML models on AWS using familiar languages and tools, enhancing your analytics capabilities to forecast future trends and user behavior.

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Our case studies

Take a closer look at our impactful solutions to understand how we’ve helped businesses like yours overcome challenges and achieve success.

Automotive
Building data lakes for an automotive software giant

We helped their team streamline data flow and consolidate diverse sources into a singular, actionable platform. This resulted in easily digestible, filterable, and accessible data, facilitating informed decision-making. 

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On Demand Service
Saved 60% cost on cloud operations management

Learn how our tailored solutions and strategic approach in cloud financial management, monitoring, and operations management led to a remarkable 60% cost saving, showcasing effective optimization strategies for streamlined cloud operations.

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SaaS
AI enabled migration assessment software for AWS Partners

VazuDev stands at the forefront of innovation in cloud services, streamlining the evaluation of cloud migation assessments, simplifying document signing, and optimizing client account management. By integrating advanced AI capabilities, VazuDev revolutionizes the migration workflow, significantly reducing both time and costs for AWS partners.

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Take the first step towards achieving data excellence.

Ready to make your data work for you? Contact us today to schedule a FREE consultation with our business team to help us understand your vision.

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Our expertise in building data analytics solutions

With a strong focus on continuous innovation, we ensure that our clients receive solutions that are not just tailored to their current needs but are also future-proof. 

Custom Data Warehouses

We design scalable, secure, and high-performance data warehouses with the ability to handle large-scale data processing tasks and derive valuable insights.

Data Visualization & Dashboards

We make complex data accessible and understandable to all stakeholders by enabling interactive reporting and dashboards, tailored to your business needs.

Intelligent Solutions that Predict

We build predictive models that use natural language processing, sentiment analysis, and GenAI capabilities to forecast trends and customer behaviors.

Data Lake Formation

We streamline the creation and management of data lakes, to merge, transform, and manage data from disparate sources, ensuring a unified data ecosystem.

Scalable Cloud-Native Applications

We build scalable, efficient, and cost-effective applications that dynamically respond to demand without the need for infrastructure management.

Our process

We follow a collaborative approach to empower your organization with the tools and understanding to leverage data analytics for informed decision-making. 

01
Discovery and Strategy
We begin with a free consultation to pinpoint your specific data needs and desired outcomes, followed by aligning our strategies with your vision, challenges, and objectives.
Outcome? Goals and expectations are aligned.
02
Solution Design and Planning
Based on the discovery phase, we build a strategic plan to meet your business objectives and start designing your data analytics solution using AWS services.
Outcome? Requirements and challenges are defined.
03
Implementation and Integration
Our experts deploy your custom analytics solutions, ensuring data is clean, consolidated, and seamlessly integrated with your existing systems for smooth operations.
Outcome? Strategic roadmap is established.
04
Analysis and Insights
We present these insights in an accessible format, through interactive dashboards, detailed reports, and visualizations, making it easy for stakeholders to understand and act upon.
Outcome? Visuals and UX ready for development.
05
Optimization and Support
Post-implementation, we continuously monitor and optimize the solution to ensure it adapts to new data, evolving business needs, and emerging technologies.
Outcome? Product is developed and operational.
06
Training and Workshops
We equip your team with the knowledge and ensure your team is fully trained to use the new analytics solutions, empowering them to make data-driven decisions independently.
Outcome? Product tested and quality assured.

Frequently asked questions

Get answers to all the common queries that businesses have while implementing advanced data analytics solutions on AWS.

What are the top use cases for Data Analytics?

Data analytics unlocks a wealth of opportunities across various sectors by transforming raw data into actionable insights. Here are some of the most impactful use cases for data analytics:

  • Supply chain analytics
  • Look after your ongoing costs & savings
  • Prove the Backup & Disaster Recovery plans
  • Price and Promotional Analytics
  • Market Basket Analytics
  • Supplier Management
How long does it take to implement data analytics?

The timeline for implementing data analytics solutions varies depending on several factors, including the complexity of your data, the scope of analytics required, and the readiness of your data infrastructure. Typically, a basic implementation may take a few weeks to set up and configure analytics tools, and integrate data sources, and begin generating insights. However, for more sophisticated analytics projects involving advanced modeling, machine learning, and custom solution development, the timeline could extend to several months. Get in touch with our team for a detailed quote on your project.

How can you help in existing Data Science & Analytics projects?

We specialize in providing comprehensive support for existing Data Science & Analytics projects. Our expertise extends to:

  • Identify the root cause of the issue
  • Fine-tuning algorithms and optimizing data pipelines.
  • Ensuring the integrity and reliability of datasets.
  • Scaling infrastructure to accommodate growing demands.
What types of data can be analyzed through data analytics services?

These diverse data types allow us to apply various data analytics methodologies, including predictive, prescriptive, diagnostic, and descriptive analytics, to extract valuable insights and drive informed decision-making.

  • Structured Data: Organized data that fits neatly into tables or spreadsheets.
  • Unstructured Data: Information that doesn't have a predefined data model or is not organized in a structured manner, such as text documents, images, videos, and social media posts.
  • Semi-Structured Data: Data that doesn't conform to the structure of traditional relational databases but contains some organizational properties, such as XML files and JSON documents.
  • Time-Series Data: Sequential data points collected over time, commonly used in forecasting and trend analysis.
  • Spatial Data: Geographical data that represents the physical location and characteristics of objects or phenomena, such as maps, GPS coordinates, and satellite images.
Is there any difference between data mining and data profiling?

Data mining and data profiling are two distinct but complementary processes in the realm of data analysis. Data mining involves the exploration of large datasets to uncover hidden patterns, trends, and insights using various statistical, machine learning, and pattern recognition techniques. It aims to extract valuable knowledge from the data to support decision-making in areas such as marketing, finance, and healthcare.

On the other hand, data profiling focuses on examining and analyzing the structure, quality, and content of the data itself. By assessing factors like completeness, consistency, and accuracy, data profiling helps organizations understand the characteristics and integrity of their data assets. While data mining seeks to extract actionable insights, data profiling provides the foundation for ensuring data quality and integrity, ultimately supporting effective decision-making processes.

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