Data Analytics and Insights

Data Analytics and Insights

Driving Intelligent Outcomes!

Better Insights for Faster Decisions!

At Locuz, we help enterprises move from being a ‚Äėdata-limited to a ‚Äėdata-driven one, thereby enabling smarter, faster decisions that result in better business outcomes.

We have been building data and analytics platforms for our customers. This spans across all workloads that can run on a single platform including Data Engineering Pipelines, Data Lakes, Data Warehouses, Data Science, Data Applications, and Data Sharing both internally and externally.

Locuz offers the broadest and most integrated portfolio of products to help enterprises acquire and organize the diverse data sources and analyse them alongside the existing data to find new insights and capitalize on hidden relationships.

Locuz' s Data Platform Delivery Approach & Methodology

Locuz, in partnership with AWS, Snowflake, Azure & Splunk offers enterprise-grade products and services to help you build cost effective Data Platforms to drive actionable intelligence. These solutions combine commercial & enterprise-grade open source technology along with Predictive Analytics (ML/DL) and real-time analytic capabilities.


Understanding the business objectives for your Big Data project as well as the infrastructure and team in place today. We'll seek answer around following major questions What are the business challenges to be addressed? What insights are required to meet these challenges? What is necessary to get there?

Output The output of the discovery phase should be a project road map addressing issues like privacy, compliance, security, single sign-on and management issues around IAM.


This phase provides the answer to "what" and "how." A successful approach starts with the development of a detailed project road map, assigning dates and milestones, and uses RACI (Responsible, Accountable, Consulted, Informed) methodology to ensure accountability.

Output Project Road Map & RACI


In this phase, the plan on paper should be transformed into functional prototypes in a secure development environment. All systems should be set up based on specifications from the design phase, and hardware and software are "burned in" in preparation for testing. In addition, all software tools must be installed and configured.

Output Completion of Data lake & Analytic infra side setup.


In this phase, assumptions will be validated and real-world scenarios are run and examined, testing sample data sets in real time. If the solution requires custom code, it should be developed here and rigorously vetted in a series of unit tests run in a consolidated process. This ensures that all scenarios have been explored and the production system delivers the expected results.

Output Streaming Dashboard & Reports


This phase must indude interoperability testing with the production network and legacy systems. During the deployment phase we'll give attention to training your team, transferring key knowledge of how the systems will run and perform.

Output Production ready Data lake & analytic environment as per scope.


To ensure ongoing stability of the system throughout its life, run-books and processes must be developed. Documentation is the critical step to set up a Big Data system for ongoing maintenance, it not only ensures the system is being maintained in but also employees can come up to speed quickly.

Output Monitoring, management and on -going operation as per SLA.

What we offer

Data Modernization

On Prem EDW migration to Snowflake/AWS Data Pipeline

Data Analytics & BI

Data Analysis Data Visualization & Reporting

DW Quality & Governance

Data Cleansing Data Enrichment

DW Manged Services

Complete Operational Support

DW Security

Identity & Access Control Encryption

Data Lake and Analytics Framework

Data Lake and Analytics Framework

Data Analytics Partnership & Ecosystem