Big Data Overview

Social media, real-time web events, GPS data points, and IoT telemetry drive the complexity of today’s business data. Whether you are dealing with semi-structured data (JSON files), unstructured data (images, video, audio files), or massive amounts of structured data (TBs of application data), Big Data is too diverse and high-volume to handle using conventional methods. As a result, storage and computing must be distributed across a network of machines. Without a Big Data strategy in place, your organization cannot leverage the tools and services available for analyzing this vast amount of new information.

Aptitive’s consultants are trained in the latest Big Data concepts and technologies, spanning from Hadoop clusters to modern cloud-based data warehouses. We have the technical expertise to tackle the challenges posed by managing and integrating large datasets and the business acumen to help your stakeholders discover actionable insights.

Our consultants will work with business users to identify Big Data opportunities that align with your organizational priorities. We will then design the architecture and processes to ingest and store the data using the tools best suited to your needs. Once the strategy is in place, we will utilize your newfound data to answer business questions such as:

  • Trend analysis and forecasting
  • Customer churn
  • Predictive maintenance
  • Customer segmentation
  • Real-time anomaly detection
  • Fraud detection
  • A/B testing

Technologies:

  • Cloudera
  • Apache Spark
  • Horton Works
  • Microsoft Azure
  • AWS
  • GCP
  • Informatica PowerCenter
  • Snowflake

Services

Working with your business to find Big Data opportunities that align with your organizational priorities

Design a detailed road map that helps you achieve your long-term vision for Big Data

Data Lake Architecture: Combine your structured and unstructured data into central hub

High-velocity data collection and storage: Ingress high speed data such as IoT telemetry or log files

Big Data analysis: Using a variety of languages (Spark, Python, Java, R, U-SQL, Polybase depending on underlying technology), extract insights from your big data and integrate them into your reporting