Big Data Analytics Solutions for Life Sciences
IMPROVING RESEARCH AND INSIGHT DISCOVERY
With big data helping accelerate growth and discovery across multiple industries, life science organizations have made great strides towards becoming analytics-driven through harvesting intelligence from their content from multiple repositories. A wide range of big data analytics platforms is available, both commercial and open source. However, a key challenge for many organizations is the shortage of deep expertise to support big data analytics initiatives. How do you acquire and prepare data efficiently? How do you derive practical insights and business intelligence from the vast amount of data you have gathered?
EXAMPLE BIG DATA ANALYTICS USE CASES IN LIFE SCIENCES
- Precision medicine
- Genomics research
- Bioinformatics research and analytics dashboards
- Pharmaceutical data lakes
CUSTOM-BUILT BIG DATA ANALYTICS SOLUTIONS
A leading provider search and big data analytics consulting and implementation, we have over 200 experts and 800 customers across numerous industries, including life sciences and healthcare. With our deep expertise in search and big data, we’ve helped a number of life sciences organizations leverage the right solutions and technologies to support their goals, including:
- Handling real-time analytics at billion-record scale cost-effectively using search engines
- Acquiring, processing, and enriching structured and unstructured data
- Advanced analytics with machine learning and proven statistical methods
- User-friendly interfaces that boost productivity and user satisfaction
- Data lake implementations for data storage, search, and analytics
- A vendor-neutral perspective – we leverage our proven assessment methodology to help clients identify gaps, select the appropriate technology stacks, and develop implementation blueprints for your custom big data analytics solution.
- Expertise in a variety of open source and commercial technologies, including Elastic, Solr, Cloudera, Google, Microsoft, Hortonworks, Hadoop, Cassandra, Spark, and others.
- Experienced, pragmatic implementation approaches
- On-time, on-budget project delivery
- Search-engine-independent technology assets for content processing and data connectivity
- Dedicated support and managed services
Contact us to discuss your big data analytics use cases and requirements.