middle management training

Tools & technologies

"If you do not know how to ask the right question, you discover nothing."
W. Edward Deming, American Engineer & Professor

  • 1What tools / technologies should I learn?
  • 2I have expertise in RDBMS how do I transition to Mongo DB or Cassandra etc.?
  • 3I have expertise in SAS how do I quickly gain expertise in R?
  • 4Is real time streaming analytics relevant for me and what is the difference between Kafka, Storm, Spark Streaming?
  • 5What are the different types of algorithms and techniques available to build a recommendation engine?
  • 6How can I ramp up my text analytics skills?
  • 7How can I leverage my data and derive powerful insights from them?

Some of our leading corporate trainings include

Hands-on training on near real time analytics

A brief overview of big data in banking and finance ...

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Big data analytics in banking

Data flows and components of Hadoop ecosystem ...

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Building advanced statistical and machine learning techniques

Scope of predictive analytics, rule induction, rule mining, visualization ...

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  • Advanced predictive analytics and unstructured data processing using R and other open source tools.
  • An interactive 2-day workshop on big data analytics.
  • A deep dive into advanced machine learning techniques.
  • A customized Hadoop training on Azure - HDInsight.
  • Customized use-cases training - Business Analytics across multiple Industries.
  • Big data analytics to handle high velocity data.
  • A customized training on big data and analytics.
  • Data Analysis on Hadoop – Hands on Training.
  • Data flows and components of Hadoop ecosystem.
  • Handling high volume and high variety data using open source tools.
  • Querying and processing large volumes of data using SQL-like tools on Hadoop.
  • Using fully open source components to handle reporting requirements.
  • Use-case discussion, optimizing warehouse throughput using Hadoop.
  • Descriptive analytics – visual analytics.
  • Scope of predictive analytics, rule induction, rule mining, visualization.
  • Market basket analysis, clustering, handling big data – R and Hadoop.
  • Bayesian techniques.
  • Taming text data.
  • Processing graphs, deep learning, use-case discussion.