Monthly Archives: November 2015

Tibco Spotfire 7, what’s new?

TIBCO Spotfire® is data analytics software designed for data exploration. It enables discovery and depiction of critical insights in data that drive real value. Spotfire has been named as Visionaries in 2015 Gartner Magic Quadrant for BI and Analytics platforms.

Tibco Spotfire has a user base in verticals like Energy, Financial Services, Manufacturing, Telecom and Consumer Goods and Retail.

Tibco Spotfire is available in 3 versions; Desktop, aimed at individuals, Cloud which is offered as SaaS model and Spotfire Platform which covers for the whole organization.

The latest version in the market is Spotfire 7 which stresses on Faster and Easier data exploration. So what’s new in Spotfire 7?

The Recommendations wizard helps the user get into data analytics quickly and easily. In-built expertise ensures the user makes great visualization choices. Setting-up the whole system is so simple even a newbie to data analytics can get it up and running in a few seconds.

Lot more design options, more modern and eye catching that help user create beautiful dashboards and data visualization. User can create custom workspaces which reflects his/her own style.

With streamlined UI elements in place, data discovery is much more faster while still offering ease-of-use.

To learn more, visit Tibco Spotfire 7, here.

An interesting Big Data Survey.

The Evans Data Corporation recently released Big Data & Advanced Analytics Survey 2015v2, some excerpts of the report was carried in this article by Louis Columbus that appeared in Forbes, titled “2015 Big Data Market Update“.

I’ve tried to highlight some of the findings here,

  • Industries that are in the forefront of creating BigData apps are Software & computing (18%), Finance (11.6%), Manufacturing (10.9%) and Retail (9.8%). One industry which is notable for not being there, Heatlhcare (4.6%).
  • Areas which are attracting most attention in Big Data, capturing higher volume of data than traditional databases (22.6%), analyzing unstructured data (21%), visualizing data (20.7%)
  • Top three reasons for movement to Big Data from traditional database, size in data (40.8%), complex, unstructured data (38.1%) and need for real-time data analysis (17.7%).
  • A surprising fact of the survey, 30.1% of developers involved in Big Data development are from companies with 100 or less employees.
  • Industries being targeted for Big Data development, Software & Computing industry (17.5%), Manufacturing (15.8%) and financial industry (14%).
  • Data sets Big Data developers are most commonly working on, sales and customer data (9.6%), IT-based data analysis (9.4%), informatics (8.7%) and financial transactions (8.4%).
  • Departments that most commonly use Big Data solutions in a company, Marketing (14.4%), IT (13.3%), R&D (13%), followed by Sales (12.6%).
  • Biggest problem related to Big Data developers are working on, Quality of data (19.2%), relevance of data acquired (13.5%), volume of data processed (12.6%).

The above are just a few I found interesting, for complete article click here.

Contextual Analysis – new dimension to BI

More and more companies have started using Business Intelligence tools to answer the question “Why” things happen the way they happen, while earlier the traditional use of a BI tool was to inform what happened, is happening or will happen in the future.

If BI tools can be used to answer the “Why” question it would very well help companies gain an understanding of why customers buy what they buy, why employees produce more/less sitting under the same environment, why stock markets fall/rise, why equipments breakdown, why the situation developed and became a crisis…

The study of “why” in any scenario is the realm of “contextual analysis”. Contextual analysis “is a method to analyze the environment in which a business operates… context analysis considers the entire environment of a business, its internal and external environment. This is an important aspect of business planning. One kind of context analysis, called SWOT analysis, allows the business to gain an insight into their strengths and weaknesses and also the opportunities and threats posed by the market within which they operate. The main goal of a context analysis, SWOT or otherwise, is to analyze the environment in order to develop a strategic plan of action for the business.” This is according to Wikipedia. The word “business” can be replaced with “environment”, “situation”, “behaviour”… to apply this definition for any area.

Now let us look at three specific examples of how inputs from contextual analysis is used in business.

Retail – to understand why customers choose products from a specific rack/aisle, why they abandon shopping carts, why increased engagement levels don’t mean increase in conversion rates, why some customers prefer coupons overs discounts… contextual analysis can explain the trend that is prevailing might be a temporary or a permannent one.

Stock market – most players in the stock market do make certain amount of prediction while making their investments on a company/scrip. This prediction is based on the understanding on why a certain board would make such a decision, to answer the question “why”, publicly available data on the board members, their voting patterns, financial data points are used in addition to external environment and public sentiment.

Energy and natural gas – Contextual analysis answers questions like why certain weather patterns lead to fall in productivity, why a piece of equipment is damaged at a certain level of operation…answering these questions can ensure workarounds or prevention to increase productivity.

To get more info on contextual analysis, suggest this article in Informationweek.