Organizations are rising in lockstep with data for data-driven decisions with the objective to drive organizational growth and seize competitive lead in the market. The path to analytical insights is dotted with challenges – Promoting lower capital expenditure involved in analytical solutions, talent constraints to leverage and manage solution, capabilities to have better control over data, and the agility to accelerate data to insights to action cycle.

Barriers to analytics

For most organizations, barriers resonate in the form of legacy data architecture that paves the way for disparate data silos. Apart from creating the disparate data silos, organizations also face the uphill task of taming external data flowing from various sources. With intelligence being limited to predetermined metrics, lot of questions go unanswered. The crux is about integrating disparate data and leveraging robust analytics tools and technologies to acquire actionable insights that can drive better business results.

Connecting our AaaS platform with your organizational Analytics needs

Our AaaS platform guides organizations to realize their objectives in terms of easing organizational pain points and promoting transformative Analytics-as-a-service model – serves as an ideal alternative to the in-house analytics solutions. Our end-to-end Analytics as a Service solution caters to different analytical purposes – From managing static to streaming data and enabling reporting, predictive and descriptive analytics to providing dashboards and reports.

Salient features of our Analytics as a service platform include:

  • Self-service platform
  • Customizable, high configurability, low threshold to get started
  • Scalable, provides safe haven for all data
  • High-performance advanced analytics engine/Facilitates valuable performance metrics in minutes

AaaS Framework for your data-to-insight journey in ‘minutes’

The AaaS Framework facilitates quick provisioning of a flexible, a highly configurable cloud-based AaaS solution. Our Analytics as a Service platform combines the most modern architecture, latest technologies and analytical tools ensuring enterprises make the data-to-insight journey in ‘minutes’ rather than ‘hours’ it otherwise might take.

The framework leads the way for a cloud-based AaaS solution extending valuable insights with:

  • Enterprise Data Lake
  • High-end multiprocessing and in-memory technologies
  • Machine learning and Data science techniques
  • Intuitive dashboards enabling easy decision making

Suit different industries, sync with different applications, offer domain-specific analytics

From retail and healthcare to logistics and financial services domain, our Analytics as a service solution offers an interface for selecting respective domains and syncs with various applications including Oracle Retail, SAS, and SAP etc. Our Analytics as a Service platform promotes domain-specific analytics with KPIs strategically handpicked for each domain along with majority of the best use-cases – from forecasting customer demand and facial analytics for identifying customer/gender/age to footfall analysis.

Our AaaS solution and Your Focus

Our platform is an end-to-end AaaS solution in the way it can suit different use cases and requirements. The platform is rich and comprehensive in the way it includes Data Integration tools, ETL tools, Analytics module, Reporting and Data Visualization Tools.

For any organizational need to infuse analytical intelligence across areas including Customer, Operations, Supply Chain, Finance etc., our Analytics as a Service platform augments different use cases and KPIs meeting varied organizational needs.

Our AaaS platform supports Video and Image analytics for Facial Recognition, Classifying gender & age to feed in real-time offers, footfall analysis. inventory management, Demand forecasting and Customer segmentation, disaster response recovery, capturing sentiments and expressions and many more.

5 Easy Steps affording seamless User Experience

Organizations need just that 5 steps to go from data to decisions. It begins with a smooth user on-boarding followed by the configuration of data sources that matter most to address a specific business case. With the execution of data mapping, services are triggered into action as in the case of allowing a specific model to run.

As the final step, you can visualize insights. For instance, if the need were to build demand forecasting, you can visualize the KPI using our Analytics as a Service solution and take critical decisions.

Business Benefits

Our Analytics as a Service platform is built for rapid mobilization, wherein it gives organizations an assured path to go from disparate data to intelligence quickly and cost-effectively. With our Analytics as a Service solution, you can reap rewards by:

  • Eliminating capital investment or high maintenance costs involved in the data-to-insights journey
  • Reducing total cost of ownership
  • Reducing costs involved in skill development and training
  • Taking advantage of low threshold to get started
  • Leveraging a scalable and flexible analytics platform
  • Reducing data to insights journey from hours to minutes
  • Promoting ease-of-use, faster adoption

How Our AaaS Services Work?

  • You can register by providing relevant details including the user details and domain
  • You can then log in to our services by providing User credentials provided during the registration
  • You can connect the ‘Source of your choice’ to initiate your Data-to-Analytics journey
    • You can use one out of 20+ sources that includes RDBMS, NoSQL, APIs, IoT sources, Files and Streaming Data etc to connect and pick data from
  • Our Mapping services then take over – We have set Target columns as needed by the KPIs relevant to each domain that help map your incoming data & sources
  • The mapped data is then sent over to the ‘Data Lake’ layer to store raw data providing basic feed for your Analytics initiatives
  • Based on data that you use for your domain and use cases, data is shared with the Machine Learning layer
  • Once the models throwing results are built, ML models are shared with the Analytics repository for housing your ML output, KPIs, Metrics, analytics use cases etc.
  • You can view your analytics results via the Visualization layer; for instance, a retail customer can view customer churn, demand forecasting or customer segmentation model outputs via visualization layer