At the highest level, the the field of statistics can be can be notionally categorized into:

• Descriptive statistics: making sense of the available data. Basically, the descriptive analytics is about understanding the known past.
• Predictive (inferential) statistics: making predictions about the unavailable data. Basically, predictive analytics is about inferring what we do not currently see: the unavailable past and of course, the future.
• Prescriptive statistics: advanced stage of predictive analytics, where future is described in the form of what-if scenarios, tied to the business specifics.

Besp0ke's Expertise:

Besp0ke has all the capabilities to rapidly advance your business in any of the directions above. Please contact us with specific inquiries.

Data Mining is about extracting information and knowledge that is dispersed and hidden across large volume of raw data.

Just like in actual mining operation, the data mining needs to process mountains of raw material in order to detect and extract the useful substance. Sometimes, it is not known in advance what one is looking for, so the search typically starts with anomalies detection and proceeds with patterns discovery and analysis.

Besp0ke's Expertise:

Data mining is one of Besp0ke's fortes. We are strong on algorythms and proficient with the mainstream methods, techniques and toolchains employed in the modern data mining. Contact us to discuss your specific business cases.

Big Data brings new opportunities, but not without pitfalls. Yes, you can achieve a near-linear growth in computational power by using massively parallel computational frameworks and commodity hardware. It's less certain about your revenue or margins because as it turns out, Big Data is not cheap even with commodity hardware and cloud computing.

If are looking to make money on Big Data capabilities you need commanding technical expertise to control your costs by making the right decisions the first time around.

Besp0ke's Expertise:

• Traditional Hadoop-based cluster computing
• Beyond Hadoop: Apache Spark cluster computing
• Massively Parrallel Processing (MPP) databases (Redshift, Vertica, etc.)
• In-database analytics
• Big Data-enabled traditional analytics: machine learning, NLP, etc.

From Twitter sentiment analysis to automatic digest generation, Natural Language Processing (NLP) analytics are becoming integral part of enterprise analytical toolsuite. The field is however a moving target and practical implementation requires significant technical expertise.

Besp0ke's Expertise:

• Leading commodity search engines SOLR and ElasticSearch
• Machine Learning open source tools
• Open Source NLP technologies