Both R & Python should be measured based on their effectiveness in advanced analytics & data science. Initially, as a new comer in data science field we spend good amount of time to understand the pros and cons of these two. I too carried out this study solely for “self” to decide which tool should i pick to get in depth of data science. Eventually, i have started realizing that both (R & Python) has its space of mastery along with their broad support to data science. Here some…

The term "Data Science" has been evolving not only as a niche skill but as a niche process as well. It is interesting to study "how" the Big data analytics/Data Science/Analytics can be efficiently implemented into the enterprise. So, along with my typical study of analytics viz. Big data analytics I have been also exploring the methodologies to bring the term "Data Science" into mainstream of existing enterprise data analysis, which we conventionally know as "Datawarehouse & BI". This…

Text (word) analysis and tokenized text modeling always give a chill air around ears, specially when you are new to machine learning. Thanks to Python and its extended libraries for its warm support around text analytics and machine learning. Scikit-learn is a savior and excellent support in text processing when you also understand some of the concept like "Bag of word", "Clustering" and "vectorization". Vectorization is  must-to-know technique for all machine leaning learners, text miner…

Data analysis echo system has grown all the way from SQL's to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by ALL) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run…

Most of Datawarehouse folks are very much accustomed with the term "Capacity Planning", Read Inmon. This is widely used process for DBA's and Datawarehouse Architects. In an typical project of data management and warehouse wide variety of audience is involved to drive the capacity planning. It involves everyone from Business Analyst to Architect to…

There are lots of topics floating around in the space of data analysis like statistical modeling, predictive modeling. There have always been questions in mind which technique to choose? which is preferred way for data analysis? Some articles and lecture highlight machine learning or mathematical model over statistics modeling limitations. They mention mathematical modeling as a next step of accuracy and prediction. This kind of articles create more questions in mind of naive…

It has been while when Big data entered into the market and buzz the analytics world. Now a day all analytics leaders are chanting about Big data applications. Since I have started with Hadoop technologies and with Machine learning one question has been bugging in mind:

Which is a greater innovation Big Data Or Machine Learning…