Data Science

Big Data Analytics Platform

Unlock Insights from Massive Datasets

Build analytics platforms that make petabyte-scale data accessible for business intelligence, data science, and operational reporting. Interactive queries, rich visualizations, and machine learning integration deliver actionable insights.

Interactive AnalyticsML IntegrationRich VisualizationsAd-Hoc Queries
55+
Analytics Platforms
<5 sec
Query Performance
300TB+
Data Analyzed
95%
User Satisfaction

What is a Big Data Analytics Platform?

Analytics at enterprise scale

A big data analytics platform provides the tools and infrastructure to analyze massive datasets that exceed the capabilities of traditional business intelligence tools. These platforms handle terabytes to petabytes of data while delivering interactive query performance.

Modern analytics platforms serve multiple user personas: business analysts who build dashboards and reports, data scientists who perform advanced analysis and modeling, and executives who need key metrics at a glance. The platform must balance ease of use for non-technical users with power and flexibility for advanced users.

Our analytics platforms combine high-performance query engines (Presto, Spark SQL) that make big data interactive, visualization tools (Tableau, Looker, Superset) that communicate insights, and semantic layers that present technical data in business terms.

Why Choose DevSimplex for Big Data Analytics?

Analytics that drive decisions

We have built over 55 big data analytics platforms analyzing more than 300TB of data across industries. Our platforms power decision-making for organizations ranging from fast-growing startups to Fortune 500 enterprises.

Analytics platforms succeed when they get used. We focus on user experience-ensuring that analysts can find data, run queries, and build dashboards without constant engineering support. Self-service analytics multiplies the value of your data investment.

Performance is critical for adoption. Users abandon slow tools. Our platforms deliver sub-5-second query responses on terabyte-scale datasets through smart architecture, optimized data layouts, and appropriate caching strategies. We prove performance before go-live through benchmarking with real workloads.

Requirements & Prerequisites

Understand what you need to get started and what we can help with

Required(3)

Data Sources

Data lake, warehouse, or other sources to be analyzed.

User Requirements

Understanding of user personas and their analytics needs.

Key Metrics

Business metrics and KPIs to be tracked and reported.

Recommended(1)

Visualization Preferences

Existing BI tool preferences or requirements for tool selection.

Optional(1)

ML Requirements

Machine learning use cases to integrate into analytics.

Common Challenges & Solutions

Understand the obstacles you might face and how we address them

Query Performance

Slow queries frustrate users and limit analytics adoption.

Our Solution

Optimized data layouts, materialized views, and intelligent caching deliver fast queries on big data.

Data Complexity

Technical schemas confuse business users and slow analysis.

Our Solution

Semantic layers translate technical tables into business concepts with clear definitions.

Scale vs. Cost

High-performance analytics can be expensive at scale.

Our Solution

Smart architecture with tiered compute, query optimization, and caching balances performance and cost.

Governance

Uncontrolled access risks data security and compliance.

Our Solution

Row and column level security, audit logging, and access controls protect sensitive data.

Your Dedicated Team

Meet the experts who will drive your project to success

Lead Analytics Engineer

Responsibility

Designs analytics architecture and leads implementation.

Experience

10+ years in BI/analytics

Data Engineer

Responsibility

Builds data models and optimizes query performance.

Experience

5+ years with Spark/Presto

BI Developer

Responsibility

Creates dashboards and visualization solutions.

Experience

5+ years in BI tools

Engagement Model

Implementation spans 6-14 weeks with ongoing support and enhancement options.

Success Metrics

Measurable outcomes you can expect from our engagement

Query Performance

<5 seconds

On terabyte datasets

Typical Range

User Adoption

80%+

Active user rate

Typical Range

Self-Service

70%

Queries without engineering

Typical Range

Time to Insight

10x faster

Vs. traditional BI

Typical Range

Analytics Platform ROI

Better insights drive better decisions and business outcomes.

Decision Speed

5x faster

Within 3 months

Analytics Productivity

3x improvement

Within 6 months

Data-Driven Decisions

80% increase

Within 12 months

“These are typical results based on our engagements. Actual outcomes depend on your specific context, market conditions, and organizational readiness.”

Why Choose Us?

See how our approach compares to traditional alternatives

AspectOur ApproachTraditional Approach
Scale

Petabyte-scale analytics

Analyze all your data, not samples

Limited to gigabytes

Performance

Sub-5-second queries

Interactive exploration

Minutes to hours

ML Integration

Built-in ML capabilities

Predictions in dashboards

Separate tools

Technologies We Use

Modern, battle-tested technologies for reliable and scalable solutions

Apache Spark

Analytics engine

Presto/Trino

SQL query engine

Tableau

Visualization

Looker

BI platform

Superset

Open source BI

Ready to Get Started?

Let's discuss how we can help you with data science.