Data Analytics as a Service
Analytics as a Service (AaaS) is a subscription-based service that provides a company with the capabilities of a fully customized analytics platform for in-cloud data analysis.
With 31+ years of experience in data analytics, ScienceSoft offers end-to-end Analytics as a Service, backed up by leading cloud services, AWS and Azure. We take care of all your data analytics elements – from data storage to custom reports and dashboards.
ScienceSoft’s Approach to Data Analysis
Areas of analysis
Types of analytics
What Makes ScienceSoft a Reliable DAaaS Provider?
Highlights of Data Analytics as a Service with ScienceSoft
To deliver the required analytics to you, we:
- Design an analytics solution with minimal cloud consumption.
- Integrate 10+ cloud services, possibly, from different cloud vendors, into a single customized package.
- Configure and develop the analytics solution’s components (DWH, ETL/ELT, OLAP, reports and dashboards), set up data management procedures, etc.
- Support and administer the analytics solution.
Making time our priority, we deliver:
- First online dashboard consisting of a few charts and tables – in 1 day.
- New online dashboard – in 4 hours to 2 days, depending on its complexity (may be longer if data cleansing is required).
- Change in the existing report or dashboard – in 2-8 hours, depending on the urgency and SLA.
Pricing Models for Analytics as a Service
- Data storage and processing in a cloud data warehouse (cloud resource consumption)
- ETL/ELT (cloud resource consumption)
- Use of a BI tool (Power BI or other) – per user
- Support and administration (% of cloud consumption)
- Changes in the DWH structure and ETL (per item)
- Adding/changing reports and dashboards (per item)
- Data cleansing (per new/changed data cleansing procedure)
- Data governance
- Master data management
(e.g., adding classifiers for analytics)
- Machine learning models development
- Data migration from the existing DWH
Grab AaaS Benefits and Be Effective Right Now!
- Enterprise-level analytics to solve your business problems.
- Analytics cost reduction due to no/little upfront investments and the elimination of continuous software license fees.
- No need for data analytics solution development and maintenance and ability to concentrate on core business processes.