10 PB
of managed data
1 million
events / second
10 years
of experience
ENTERPRISE ANALYTICS
Get to insights faster
Before realising business value with analytics, companies have to build a platform and fill it with data. This investment is necessary to consistently generate insights at scale. We use our starter kit and years of experience to quickly build the analytics platform and implement data pipelines, reducing the cost and risk of the initial investment. That way, our clients can get to value 10x faster and focus on what’s important for business: business intelligence, data science, and data driven decisions with machine learning.
EDW CLOUD MIGRATION
Reduce cost and increase scalability
Traditional on-premise EDW software, such as Teradata, Netezza, or mainframe-based DB2, is getting prohibitively expensive and can’t efficiently scale to the new analytics use cases. By migrating data pipelines and reporting to the cloud, you can reduce total cost of ownership, take advantage of onboarding new data sources, implement real time streaming data pipelines, and dynamically scale to increase efficiency of data scientists.
DATA LAKE CLOUD MIGRATION
Accelerate innovation
Very few companies should be in the business of managing on-premise data lakes. High cost of maintenance, stability issues, coupled with lack of scalability and limited technology stack options for DataOps and MLOps, they slow down data analysts. Migrating on-premise data processing to the cloud based solution reduces total cost of ownership, increases data quality and accessibility, and re-focuses company resources on building differentiating value.
DATA LAKE UPGRADE
Increase data quality and accessibility
Basic data lake is no longer sufficient to implement effective analytics at scale. Too many companies fill in in the lakes only to realize that the data is difficult to use. To unlock the value of data, upgrade your data lake with data governance, data quality, catalog and lineage, access layer, implement stream processing, and deploy an AI platform.
DATAOPS AND MLOPS
Become data driven organization
Getting value from data is hard without needed skills, culture, process, and tools. Similar to how DevOps streamlines application delivery processes, DataOps and MLOps can increase the quality of data pipelines and help data scientists consistently and repeatedly turn data into insights.
Our clients
RETAIL
HI-TECH
MANUFACTURING & CPG
FINANCE
HEALTHCARE
Customer Success Stories
On their quest to future-proof their smart manufacturing operations and create a more connected, predictable environment, Jabil Inc, a leading global manufacturing solutions provider, required a cloud-native data platform to meet these goals.
Grid Dynamics, partnering with AWS, took the task head on and implemented a unified Analytics Platform in the cloud with a series of Industry 4.0 AI solutions in record time. Besides recognizing business value within weeks, the platform improved the speed of anomaly detection from days to hours, made business intelligence insights available on demand, and facilitated the consolidation of data analytics efforts on a single platform with cloud-native technologies and the MLOps process for efficient flexibility, scalability and automation.
Get from raw data to business impact faster
Analytics platform accelerator provides a set of pre-integrated capabilities covering end-to-end data lifecycle from ingestion to machine learning including batch processing and streaming data ingestion, data processing, data transformation, data management, catalog and lineage, data pipeline orchestration, data preparation, data warehouses, reporting, as well as AI platform. It is built on the best of breed combination of open source software, saas platforms, as well as cloud-based services. The solution has been battle tested in company-wide numerous deployments in Fortune-5000 companies and technology startups, satisfying the strictest performance and security requirements.
10
petabytes of data
1,000,000
events / second
100s
data sources
1000s
managed data pipelines
High
quality and accessibility
Technology stack
Analytics platform industries
We helped Fortune-1000 companies unlock the full potential of data.
Technology and media
Data is the main corporate asset for many technology and media companies. It could come from customers or IoT devices, but it should be efficiently and securely captured, managed, and made available for consumption. High performance, scalability, and quality are paramount in these cases. We have helped #1 media company in the world to design and develop analytics at scale.
Retail and brands
High conversion, profitability, and inventory turns are not possible without deep understanding of customer, product, inventory, and supply chain. We helped Fortune-1000 retailers and brands manage and take advantage of their data assets. We increased efficiency of analytics by moving data pipelines to the cloud, increased conversion with personalization, optimized inventory, and generated millions of dollars in incremental revenue with real time offers.
Finance and insurance
Financial services are inherently data driven organizations. With banks and insurance companies starting their journey tens of years ago, many are stuck with fractured legacy on-premise systems that are prohibiting scale and slowing down innovation. We helped companies take advantage of their data assets by consolidating data pipelines and migrating traditional EDWs and data lakes to the cloud.
Read more about analytics platform
Accelerate the journey to modern analytics
We provide flexible engagement options to design and build analytics platforms and AI use cases at scale. Clients take advantage of our starter kits to increase their speed to insights and reduce the risk. Contact us today to start with a workshop, discovery, or PoC.
Workshop
We offer free half-day workshops with our top experts in application modernization to discuss your stream processing strategy, challenges, modernization opportunities, and industry best practices.
Proof of concept
If you’ve already identified a specific use case for application modernization, we can start with a 4–8 week proof-of-concept project to modernize a few key applications to deliver tangible results for your company.
Discovery
If you’re at the application modernization and cloud migration strategy development stage, we can start with a 2–3 week discovery phase to perform an analysis of your existing application portfolio, create a target architecture, and build a modernization roadmap.
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