AWS Consulting Partner

Cloud and Big Data Analytics for Life Sciences and Pharma using AWS

Axtria is an Amazon Web Services (AWS) Consulting Partner offering the full range of Business Consulting Services coupled with savvy Cloud and Big Data Analytics. Our high success record is built on our unparalleled domain knowledge in Life Sciences and Pharmaceuticals.

We pioneered and continue to deliver cutting-edge analytics and software solutions to help global companies effectively convert data to insights and manage their day to day commercial operations. These business solutions deliver significant benefits of cost, agility, and scale.

CAPABILITIES

Migration to the Amazon platform

Cloud-based Data Warehouse

Data Lake
Implementations

Analytics Workbench on the Cloud

CUSTOMER SUCCESS

USE CASE 1

Expertise

RE-DESIGN
(DWH modernization using AWS cloud technologies)

Client Description

A top 2 Pharma company’s growing portfolio demanded agility, cost economies, scalability, and innovation in data and insights.

Client Challenge

  • Long data to insights cycle time
  • Low data quality
  • Inefficient business rule management
  • Limited ability to adapt to future needs

Axtria Approach

  • Next generation analytics data lake on AWS integrating ~40 data sources
  • 250 weekly and 140 monthly extract files to downstream users
  • Business Rules Management System with 22 rules
  • Early Warning System with 48 DQM dashboards

Technology Stack

  • Environment: AWS EC2, RDS, Redshift, Hive
  • ETL: Talend, SQOOP, Python, Spark
  • Reporting: Tableau
  • Worfkflow: Tidal
  • MDM: Reltio

Benefits

  • Cost savings of ~30%
  • Reduced weekly cycle time from 5 days to 1 day
  • Change management in the hands of the business users
  • Automated DQM process
  • Ability to add new-generation data sources

USE CASE 2

Expertise

RE-BUILD
(Incremental Approach – Initially build a data lake, then iteratively add modules)

Client Description

A top 5 US Pharma client wants to create a best-in-class data analytics environment tightly coupled with analytics & visualization under a governance framework

Client Challenge

  • 3-4 PB of structured, unstructured and clickstream data from 300+ data sources leading to high data processing and integration time
  • No single source of truth and high error rate.
  • Analysts spend time on data processing rather than analytics

Axtria Approach

  • Analytics Data Lake on AWS integrating all major databases (Commercial, Managed Markets, Patient )
  • Supporting 50+ dashboards for 200+ users, expandable to all therapeutic areas.

Technology Stack

  • Environment: AWS EC2, RDS, Redshift, Hive
  • ETL: Informatica, SQOOP, Alteryx, Python, Spark
  • Reporting: Tableau
  • Worfkflow: Control M

Benefits

  • Faster onboarding – 2 TB data / month
  • 3-4 PB of data processing in hours with predefined plumbing
  • Predefined KPI & ad hoc analytics for end user consumption
  • Enabled a powerful analytics workbench for AI and Data Scientists

USE CASE 3

Expertise

RE-HOST
(Migration of “As-is” solution to cloud technologies and then optimize)

Client Description

A leading pharma company, wants to migrate on-premise Teradata DDW on to the next generation cloud platform to reduce TCO and increase scalability

Client Challenge

  • Integration of New Data Sources
  • End-to-end process execution lengthy and inflexible
  • 10 TB in motion ingested from 67 data sources
  • Manual data validation by business

Axtria Approach

  • Next generation Commercial DDW on AWS cloud technologies
  • Setup an in-built DQ system and overall governance regime
  • 70 downstream applications with over 7000 views.

Technology Stack

  • Environment: AWS EC2, RDS, Redshift, Hive
  • ETL: Matillion, Spark, S3, SNS, Glue, CloudWatch

Benefits

  • 33% performance gains in end to end cycle time
  • Automated validation process to identify and resolve data anomalies
  • Less time on data analysis and more on insight and analytics
  • Vertical & horizontal scalability

USE CASE 4

Expertise

ANALYTICS WORKBENCH
(Data to Data Science eco-system)

Client Description

Advanced analytics team of a top 10 pharma wants to develop a best-in-class data analytics environment on a cloud based data lake. Create a next best action (NBA) model for a Multi-channel marketing eco-system.

Client Challenge

  • Unable to do multi-channel marketing analytics as there is no centralized data model
  • Manual intervention in processes – low analyst effectiveness
  • Onboarding and integrating different data sources is slow and expensive

Axtria Approach

  • Analytics data lake on AWS integrating all major sources of marketing channel data
  • Analytics workbench on AWS which allows self-service analytics
  • A Next Best Action (NBA) model created using random forest and machine learning

Technology Stack

  • Environment: AWS EC2, RDS, Redshift, EMR, S3
  • ETL: Lambda, Spark, Python
  • Analytics: R

Benefits

  • Query execution time reduced by 60%
  • Tight integration between data warehouse and analytics platform
  • Productivity of analytics team increased by >80%
  • Scalable to include more analytics models

Let Us Show You What Axtria Can Do For You