Hadoop Case Study
Learn how we helped a leader in the Transportation and Logistics domain address their Big Data Challenge.
Aptude specializes in Apache Hadoop implementation and integration for enterprise environments. We chose Hadoop as a platform for its flexibility, scalability, and cost-saving benefits for our clients.
Hadoop is a mature, proven platform for handling big data that is challenging for relational databases to manage.
By leveraging our partnerships with HortonWorks, MAPR, Cloudera, Microsoft, and Oracle, Aptude has a comprehensive set of tools and services available at our disposal for Hadoop implementations into any environment.
Apache Hadoop is a big data solution which allows for distribution of processing across server clusters. There are many use cases for Hadoop where it can provide solutions for handling high volume/velocity data that is not suited for existing relational database solutions.
As an open-source software, it provides a scalable, cost-effective solution that can consume any type of data and prepare it for use with your choice of business intelligence and analytics packages.
Confused about Big Data?
Read about our insights into how Big Data can fit into your organization's environment.
Benefits of a Hadoop Integration
Scalability & Reliability
Hadoop stores data in a distributed storage environment; servers in a cluster are running individual instances of Hadoop, working as nodes in the system. If a server goes down, Hadoop will redirect processes to the other servers. The scalability of Hadoop allows you to add as many servers and resources to your Hadoop clusters as you want without disturbing current operations.
Efficient & Cost Effective
The HDFS storage component of Hadoop makes it one of the fastest platforms for handling complex, large data files regardless of their structure. As a parallel computing software, Hadoop harnesses the power of multiple servers running in tandem, allowing for substantial savings on hardware procurement.
Hadoop can integrate into both Microsoft and Unix/Linux based environments, capable of running on Apache or IIS web servers. Additionally, it can consume any type of data, regardless of being structured or not. Multiple data sources can be accessed, which enables aggregation from various systems and use of your preferred analytics and data visualization software.
- Store all your data and data types in a single system
- Cost Savings – Large savings in storage, licensing and hardware
- Flexibility – Schema on read (not write), Scalable as needed
- Open Source Platform
- More data, more analytics, more insight
Aptude Hadoop Solutions
With over 16 years of experience in IT consulting, Aptude provides the experience and knowledge of software integrations within complex environments required to properly integrate and implement Hadoop solutions. Aptude is an Oracle Gold Certified partner and has recently partnered with Cloudera for enhancing our Hadoop solution offerings. Our expertise in Hadoop integration allows our experts to provide valuable business solution insights.
Aptude has chosen Hadoop as a platform because of how accurately and seamlessly it addresses problems related to big data. Using the MapReduce architecture, Hadoop has matured into an ideal solution for storing and processing big data with minimal risk and increased efficiency. The software has been designed specifically for handling data coming at high velocity and from variety of sources in enterprise environments.
Could your organization benefit from Hadoop?
Below are some common Hadoop use cases. If your environment matches any of these situations, then Hadoop may be the right solution for you.
- You have valuable data you’re not capturing (structured, unstructured data, semi-structured data, other)
- Storage Licensing Cost or Database Licensing Cost are prohibitive to you keeping and analyzing large amounts of data
- Can’t complete data processing fast enough – ETL performance issues - missed targets
- You would like to reduce data storage costs or free-up data warehouse space/resources
- Business decisions are made on data samples or outdated data; only able to retain a small % of your data.
- Data is constantly being migrated between separate systems
- EDW is at capacity – slow performing and reaching bottlenecks
- Business is requesting analysis on a much wider set of data; long-term data retention, without disposal or tape archiving
Getting Started With Hadoop - Aptude's Proof of Concept
Many organizations struggle with getting started with Hadoop. They potentially see the value of implementing a game-changing infrastructure like Hadoop, but need a demonstration of how it will integrate and perform with their systems. We have discovered an ideal solution is our 4-6 week Proof of Concept (POC) phase which will provide a low-cost validation to stake-holders including Sr. Management and IT.
POC Steps Include:
- Use Case Discussion / Analysis with Benefit Identification of POC
- Infrastructure Determination
- Hadoop Server Hardware requirements
- Cloud based or internal Hadoop Farm determination
- Team Member Identification / Communication Plan
- Hadoop Cluster Identification and Configuration determination
- Software/Hardware Architectural Design
- Data Flow/Work Flow Architecture –
- Hadoop Design – Processing
- Analytics Design
- Development Phase
- Testing Phase
- Implementation Phase
- POC Validation - Was the POC successful?