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Harness the cloud's power and unlock your data's value with scalable, flexible, and optimized solutions.

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Cloud Providers

We offer services for a wide range of use cases on the cloud, including data backup, disaster recovery, email, virtual desktops, software development and testing, big data analytics, and customer-facing web apps, especially for mid market & small medium enterprises in every sector.
Compare AWS, Azure and Google Cloud.

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Data Solutions

We offer a range of data solutions to meet your requirements mid market or small medium enterprise in any sector to use data to rethink your operations. Our speciality includes purpose-built services that offer the best price-performance, scalability, and lowest cost for everything from data migration to data storage to data lakes and warehouses.

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Big Data Processing and Analytics

Employing Big Data and analytics solutions, Justo allows mid market & small medium enterprises to work with enormous volumes of multi-formatted data, including structured, semi-structured, and unstructured data. Mid market & small medium enterprises, therefore, can supplement huge and diversified data sets to find precise patterns and correlate data points in consumer behaviour analytics, predictive analytics, and AI/ML-enabled forensic data analysis. Incredible big data statistics

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Data Management Strategy

We'll evaluate your company's current data and analytics problems and create a comprehensive data strategy with a step-by-step implementation plan. In a shifting corporate landscape with unstable markets and new technologies, we help you constantly update your data strategy. This update guarantees secure and consistent data and the establishment of a comprehensive data governance programme.

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Compare AWS, Azure and Google Cloud.

Cloud Service Providers
Amazon Web Services (AWS) Microsoft Azure Google Cloud Platform (GCP)
Age of the Platform
20 years 14 years 11 years
-Extensive, mature offerings
-Enterprise friendly services
-Open and flexible
-Global Reach
-Integration with Microsoft Tools
-Broad feature set
-Ranks first in development and testing tools
-Open source support
-Hybrid cloud
-Open-source support and portability
-Discounts and flexible contracts
-Designed for cloud-based businesses
-Dev Ops expertise
-Difficult to use
-Overwhelming options
-Cost management
-Less efficient management tooling
-Less "enterprise-ready"
-Entered the IaaS market late
-Less data centres around the world
-Fewer services and features
Market share
62% 20% 12%
Per hour Per minute Per minute

Data Lakes vs. Data Warehouses

S. No. Areas Data Lakes Data Warehouses
1 Data Storage A data lake contains all of an organization's data in a raw, unstructured form, stored indefinitely. Structured data that has been cleaned up and processed and is ready for strategic analysis can be found in a data warehouse.
2 Users Data scientists and engineers that like to analyse data in its raw form in order to generate fresh, original business insights frequently use data from a data lake. Managers and business-end users often retrieve strucutred data from a data warehouse to get insights from business KPIs.
3 Analysis Predictive analytics, machine learning, data visualization, BI, big data analytics. Data visualization, BI, data analytics.
4 Schema In a data lake schema is developed after the data is collected, hastening the data capture and storage process. Before the data is stored in a data warehouse, the schema is established. The processing of the data takes longer as a result.
5 Processing ELT (Extract, Load, Transform) processing. This method involves removing the data from its original location for storage in the data lake, and only structuring it as necessary. ETL (Extract, Transform, and Load). Data is taken from its source(s), cleaned, and then processed in this process so that it is suitable for business-end analysis.
6 Cost Storage expenses in a data lake are relatively low. Additionally, managing data lakes takes less time, which lowers operational costs. Data warehouses are more expensive than data lakes and demand more management effort, which drives up operating costs.

Incredible Big Data Statistics

  1. $274 billion. This is the value of the global big data and analytics market.
  2. Every day, around 2.5 quintillion bytes (10^18) of data are produced.
  3. Currently, the total amount of data in the digital cosmos exceeds 44 zettabytes (1 zettabyte = 1 billion terabytes).
  4. User-generated data makes almost 70% of all data in the globe.
  5. Yearly end-user spending on cloud computing is close to $500 billion.