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Discover tangible generative AI industry use cases in our new ebook

Analytics Platform

Increase speed to insights. Manage enterprise data assets, migrate from on-premise EDW to cloud, improve data accessibility and quality, and increase the return on investment with our solution and starter kit.

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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

Starter Kits

Analytics Platform Starter Kit for GCP
Build a production-ready, modern analytics platform within weeks on Google Cloud Platform. Improve data accessibility and quality, increase speed to insights, and achieve significant ROI with our starter kit.
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Analytics Platform Starter Kit for AWS
Build a production-ready, modern analytics platform within weeks on AWS cloud. Improve data accessibility and quality, increase speed to insights, and achieve significant ROI with our starter kit.
Read more
Analytics platform Starter Kit 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. analytics data platform - data lake, Grid Dynamics
10
petabytes of data
1,000,000
events / second
100s
data sources
1000s
managed data pipelines
High
quality and accessibility

Technology stack

Capability Open-source 3rd party AWS GCP Azure
Data lake
Messaging
EDW N/A
Access layer N/A
Orchestration
Data catalog
Data quality
Application platform
AI platform
Capability Data lake Messaging EDW Access layer Orchestration Data catalog Data quality Application platform AI platform
Open-source N/A
3rd party
AWS
GCP N/A
Azure
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Analytics platform industries

We helped Fortune-1000 companies unlock the full potential of data.

hi-tech icon
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 icon
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 icon
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

From data lake to analytics platform
In this article we review the industry journey from basic data lakes to modern analytics platforms. We also explore what capabilities data driven enterprises need to increase the productivity of their teams.
Read more
5 technology enablers for DataOps
This article describes how to consistently generate actionable insights with DataOps and MLOps and what tools are required to support it.
Read more
Why you need data quality automation to make data-driven decisions with confidence
With growing numbers of data pipelines, data quality is important now more than ever. In this article we describe how to add it to your toolbox.
Read more

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 big data and analytics to discuss your stream processing strategy, challenges, optimization opportunities, and industry best practices.

Proof of concept

If you have already identified a specific use case for big data or fast data, we usually can start with a 4–8-week proof-of-concept project to deliver tangible results for your company.

Discovery

If you are in the stage of requirements analysis and data strategy development, we can start with a 2–3-week discovery phase to perform gap analysis, design your solution, and build an implementation roadmap.

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