ATI Blog

Business Analytics a fast growing field in developing nations and in India you can see sudden growth of analytics in the last decade. The range of tools go from the simple excel to the more complex ones like statistic etc.  Here, we shall try to see a glimpse of various analytical tools used in the industry also specifically by some companies.

Let’s look at the top analytical tools in the business world

1.  Excel
2. SAS
3. SPSS
4. Statistica
5. Salford Systems
6. KXEN
7. Angoss
8. Matlab
9. R
10. Weka

Excel : Every business unit have access to MS Excel. This is an excellent analytical, reporting and dash-boarding tool. Excel can handle tables with up to 1 million rows

SAS : SAS is the elephant of analytical industry and it’s been there for long. This tool has been used by most of the important analytical companies of the world. It is most popular irrespective of its high price.

SPSS: This tool is most famous for its GUI based application. It is easy to use and understand. It is point and clicks and has advanced modelling capabilities

Statistica: It is developed by statsoft. Statsoft also has a website online which has most of the statistics concepts neatly explained there. Statistica supports wide variety of analytics technique on the lines of CRISP-DM (Please look up for this one online. This is the bible of any analyst). The GUI though is not so user friendly here

Salford Systems : Provides predictive analytics and data mining tools for the industry. It specialises in regression algorithms

KXEN : They are specializing on automated analytics. Their products are comparatively easy to use. The result however is rather difficult to understand which a drawback is for them

Angoss: They have advanced decision tree algorithms. The GUI is easy to use

Matlab:  It has more of mathematical applications. They have add on features which helps to make the organisation fine tune the tools to specific areas of functionality.

R : This is an amazing tool for statistical computing and graphics(Graphics after Matlab). This is an open source ware and is widely used by the academic community. This is updated by the user community and can find 800 and odd packages for various functionalities.  You can find packages for almost anything and everything. You have many GUIs available with R, Rattle is one of them for statistical analysis.

Weka: This is another free ware like R. The software is written in Java and contains a GUI for interacting with data files and have visual effects and graphics.

That was in a nutshell the tools used and the important companies in the analytical industry. This was only a gist. It’s a booming field for the coming years in India. Let’s leverage the maximum from this. ATI will be a part of this humbling journey to empower professionals.

1. They don’t spend much time in developing traditional algorithms anymore (e.g. search engine). They don’t reinvent the wheel, they re-use existing algorithms, even though they could do a better job by re-inventing these old algorithms. But they think at significantly improving existing algorithms (e.g. search engine), both from a business and technical point of view. Sometimes they even do a bit of hacking and reverse engineering.
2. They spend a lot of time identifying useful data sources (most of the time, external sources), and checking how they could be exploited and leveraged.
3. They develop meta algorithms: that is, algorithms that rely on lower level techniques such as taxonomy creation, spell check, keyword associations, news feed aggregation etc. They blend these low level algorithms to produce automated high end products.
4. Modern data mining is to old data mining what coding in Python is to coding in assember, Perl, or C.
5. These data miners don’t call themselves data miners anymore: they are statisticians, scientists and data miner all at the same time, combining all these roles in one person. Indeed, they are even business people and sales guys (selling internally – to their boss and employees reporting to them, and externally – being invited at important sales calls by their company).
6. Many times, they succeed not by analyzing data, but by applying analytic thinking to business problems. Example: we’ve increased our signups by a factor 3 on our network thanks to analytic thinking – however no data was leveraged to get to the action resulting in signups improvement.
7. They sometimes develop great products without having to produce one line of code: our news feed optimizer is a good example of a technology that was developed without writing any code, but instead relies on widgets to distribute the news, manual selection of good feeds, and intelligent use of feed aggregators such as twitterfeed or feedburner.
8. They find the information they are looking for on the web (and more and more from social networks as opposed to Google), but not from books nor University training.
9. They are working on algorithm speed optimization and scalability, even (and especially!) when developing prototypes.
10. They are thinking so much out-of-the-box, that they are not generally a good fit for the corporate world. Instead, they become successful entrepreneurs.
11. They are domain experts more so than coding experts. But they are also generalists across many fields and many tech skills (e.g. all of them are very familiar with SQL and R). At the same time they have deep expertise in a few (one or two) specialized domains and programming languages.

Post By – Vincent Granville – Vincent Granville’s Blog

We are in world where we are accustomed of having information at their fingertips. We also have the need to identify key performances of our company at a glance. This is where we have the need to create or build dashboards. There is no better platform than MS Excel for building a simple dashboard with simple tools. A dashboard consolidates information that is pulled from multiple data sources and transforms the information into a visually rich interactive chart.

The following video demonstrates a simple dashboard created for the Autism Society of India.

I was going through some videos on Analytics and found this fantastic video which has explained Analytics in such a simple animation.

The data mining cup is a case competition in Data Mining and is state-of-art initiative in the corporate world. This could include a case study of a real life problem and the best solution is adjudged by the solution proposed. The case will be given to the participants on
10th Feb, 2011 and the solutions have to be submitted by
27th feb, 2011. The participants can use any statistical tool in arriving at a solution.

Rules and Guidelines

No registeration fees

Prize Money : Rs.1500/- worth Flipkart gift voucher per team
Team size : 3 (Individuals can also participate)
Last date for submission : 27th feb, 2011