Don’t Become Inundated By Data
As the digital age progresses, the volume of Big Data generated and collected grows and accelerates exponentially. Analyzing this rapidly growing data is problematic with traditional analytical tools. If we want to bridge the gap between data being generated and data that can be analyzed, an innovative approach is required.
PROBLEM
The vast Big Data products landscape presents a challenge to every project. It’s difficult to choose the right tools and technologies when building a Big Data platform. The deluge of Big Data is another part of the problem. You need to be able to choose the Big Data technology that suits your needs and integrate the new systems with the old ones. If you are not a Big Data expert, it’s difficult to keep up with the latest trends.
SOLUTION
A Big Data platform ensures all your data is properly stored and analyzed. Our experience and methodology allows us to conduct a proper tools evaluation, and choose the correct architecture pattern and integrate it with your existing Big Data platform or infrastructure. We design vertical and horizontal prototypes to ensure that tools and architecture are selected according to the business and technical needs. We then proceed with a roadmap for growing and developing your Big Data platform.
PROBLEM
The amount of data is continuously growing in your organization, but the volume of information that is really analyzed is extremely low. Your existing data infrastructure is not suitable for the modern analytical patterns, like real-time analytics, streaming process, data discovery and visual analytics. To make matters worse, the IT and business leaders are not fully aligned to improve the situation.
SOLUTION
We bridge the gap between IT organization and business that unveils data potential for insight-driven decision making. We help point you in the right direction in terms of which tools and analytical patterns to use by analyzing different kinds of characteristics and requirements. We will take your data analysis to the next level, thus ensuring your business decisions become data-driven.
Big Data on AWS
Tools we Use
Explore a complete list of AWS products for Data Warehouse solution here
Deliverables
- Reviewed business goals and drivers for the modern Big Data platform
- Data sources documented according to 4V requirements (volume, variety, velocity, veracity)
- Tools evaluation including vertical and horizontal prototypes
- Strategic roadmap for developing your Big Data platform
- Big Data platform that corresponds to the business goals and architecture drivers
Full Cycle Services
AUDIT
We’ll evaluate your current Big Data solution according to your business goals and architecture drivers, including ingestion process, data sources, tools, etc.
CONSULTING
Based on the audit results we’ll provide you with a roadmap for developing and improving your current Big Data solution.
DELIVERY
We’ll deliver a solution or make performance and architecture improvements according to a roadmap.
TRAINING
“How to” training session will guide your engineers and support team, helping them learn how to operate the solution.
Typical Project
- Interview your team to clarify high-level business goals and drivers
- Review data sources and the entire data ingestion process
- Identify performance, security and other kinds of the problems
- Evaluate solution architecture and technology mapping
- Evaluate business intelligence and reporting requirements
6. Define roadmap with the milestones, timeframe and budget
7. Fix issues, optimize performance and architecture
8. Conduct tools replacement and migration to the AWS Cloud if necessary
9. Transfer solutions to the engineering and support teams
Benefits
Optimized data storage
Evaluated technology stack
Defined Big Data strategy & roadmap
Reduced queries and reporting execution time
Automated data ingestion process
Flexible Big Data solution ready to scale
Testimonials
“Squadex helped us build a Big Data solution which eliminated a lot of manual work and increased the quality of the data we provide our customers with. Now we look further for an even deeper optimization of data processing and connecting more and more data sources.”
Prayag Narula, CEO at LeadGenius