What matters most in the exploding universe of data and technologies to process it – is Time to Value. We are surprised by the number of organizations that refrain from investments into their own Big Data solutions just because they cannot assess how long the journey will take.
At the Sensemaking Lab we have devoted several years of development efforts to establish a Big Data Analytics and Sensemaking Platform and an information governance framework to decrease time to value for our clients. It allows us to deliver our solutions and prototypes on premise or in the cloud with almost no upfront investments into application integration or infrastructure. In several cases, with our Platform and Rapid Prototyping process we were able to decrease the time to value by 10 times compared to our best competitors – from several months of data integration to just 3-5 weeks.
Compared to traditional OLAP-based fit-for-purpose approaches to business analytics that can work only with structured prepared datasets, we take a holistic augmented approach to ingest and derive insights from all available data. For us Big Data means All Data, which means we can ingest and preprocess literally any type of data, at any volume and incoming velocity rate.
The Platform seamlessly integrates:
- Industry-leading IBM Big Data Analytics technologies – IBM Infosphere BigInsights, IBM Infosphere Streams, SPSS, DB2
- Open-source toolkits and libraries for data analysis and integration – UIMA, OpenCV, R, Weka and several others
- Proprietary components that automate and ease a number of data processing tasks – crawlers and connectors, converters, feature and keyword extraction annotators and dictionaries, data-specific processing pipelines (for web pages, natural language texts, application logs, social media content and many more).