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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.

Business Intelligence Tool series – Tableau, Part – 2

Here is the part 2 of the series on Tableau BI platform.

Tableau Dashboards
Using Tableau, users can create interactive real time dashboards and stories. Dashboards are a combination of individual data visualizations. Tableau Dashboards have data visualization best practices built in.

Users can interact with a dashboard by filtering data, drilling down on specific elements etc. Sharing of dashboards is also very simple and is just a click away from embedding them into company portals, websites etc.

An interactive dashboard created using Tableau Desktop can be used to display the sales and profits of various products in a store. It can display the following visualizations:

Sales per product category as a Tree Map
Sales per product sub-category as a Heat Map
Profits per product category as a pie chart
Profits per product sub-category as a Bar Chart
Sales/Profit per customer segment as a Bar Chart

In this manner the sales and profit values for different consumer segments like Corporate, Home Office etc. across different regions like East, south etc. can be visualized using Tableau Dashboards.

Tableau Story Points
Tableau goes one step beyond the dashboards with the introduction of Story Points. Using Story Points, users can build a narrative or a story using the data visualizations and dashboards for easier sharing with others. People find it easier to grasp and remember concepts when told in the form of a story like in case of books or movies. Story Points enables users to share data in the form of a story. As said by Francois Ajenstat, Tableau’s director of product management, “People tend to remember concepts through stories. It’s the oldest form of communication. You can highlight interesting points in your views, and put it together in a sequence with a narrative.”

How it works
Most data visualization presentations today using other Business Intelligence involve users copy pasting the visualizations to a PowerPoint presentation. Tableau’s story point template has the option of having multiple blocks with captions arranged in the form of a strip at the top and a pane for arranging visualizations and dashboards. Visualizations can be easily added, removed and arranged in the pane with simple drag and drop motions, and required coding or programming knowledge. Users can click through the blocks sequentially to move through the panes. As in the case of dashboards, story points are fully interactive with options for filters and other controls.

Tableau Server
Tableau Server is browser- and mobile-based insight anyone can use. Publish dashboards with Tableau Desktop and share them throughout your organization. It’s easy to set up and even easier to run.

Features:

Turn everyone into your best analyst with interactive dashboards in a web browser or mobile device.
Embed dashboards in company portals across your business.
Comment on dashboards to share your findings.
Subscribe and get regular updates.
Filter data, drill down or add entirely new data to answer to your analysis.
Edit any existing view, on the web. And do it all with Tableau’s blazing fast data engine so you get your answer when you ask it.
Publish shared data connections from Tableau Desktop. Define data sources, add metadata, and author entirely new calculations and data fields for everyone to use.
Publish shared data connections from Tableau Desktop. Define data sources, add metadata, and author entirely new calculations and data fields for everyone to use.
Have permission settings to manage access to data connections.

Flexible data architecture
Tableau Server leverages fast databases through live data connections, or can extract and refresh your data in–memory with its blazing fast data engine.

Automatic updates
Refresh local data on schedules, at set intervals, or incremental levels. Or just refresh it all. Get alerts when data connections fail. Set up subscriptions so you get your data when you want it, as often as you want it.

Embedded analytics
Embed dashboards within your organization’s existing workflow. Whether you need native database connectors, APIs or a suite of authentication methods, it’s in the bag.

Scalable
It scales with both hardware and memory, and comes with many features to ensure it is a reliable enterprise backbone.

Mobile
Author a dashboard once; view it anywhere, on any device. All dashboards are automatically optimized for mobile tablets without any programming. Use familiar tablet gestures to view and interact with dashboards in mobile web browsers or using native iPad and Android apps.

End of Part 2 of 2.

Business Intelligence Tool series – Tableau

In this blog series we plan to feature some popular BI platforms, in the first of the two-part series we bring to you Tableau.

Tableau is a visualization tool with a focus on Business Intelligence. It is built on the Visual Query Language for Data, pioneered by tableau as VizQL™. VizQL™ is a technology that optimally converts the user’s drag and drop action into a database query and outputs the results visually in the form of data visualizations.

Analysis and visualization at the speed of thought
Another impressive technology of Tableau is its data engine capable of visually querying petabytes of data with billions of rows in mere seconds, or to put it more aptly, at the speed-of-thought. Combined with the drop and drop functionality, it enables users to follow their train of thought in analysing data. It also allows users to connect to a data source and obtain the visual analysis without any coding or scripting.

Connecting to data
Tableau allows users to connect to data in multiple ways. Using its powerful data engine, users can connect to multiple sources of data at once, connect live or take a snapshot of the databases to take advantage of its breakthrough in-memory architecture etc. The types of data sources that can be connected to Tableau can be found here.

Why Tableau?
Tableau has been the industry leader in Business Intelligence products and solutions for the past two years. Each year, Gartner analyses every vendor in the Business Intelligence and Analytics market. Their research has particular significance because it often identifies the innovations that drive the market. As part of that report, Gartner also releases the Magic Quadrant, which shows the relative positions of the market’s competitors.

Tableau has once again been recognized as a Leader in the Magic Quadrant for 2014.

Product Offerings
Tableau offers three types of products namely, the Public, Personal and Professional Edition. The Public Edition is a free edition that allows workbooks and dashboards to be published ONLY to Tableau’s public website. The personal edition, while allowing workbooks to be saved locally, does not have the ability to connect to databases. The Professional edition is the full-fledged product from Tableau.

Part 1 ends here

Big Data in Banking and Finance

The movement from in-person to on-line banking and the regulatory requirement to maintain historical data has lead to huge and diverse volume of data being collected by Banks and financial institutions. In simple terms, data collected by banks is estimated to grow by 76% in 12-18 months. Though challenging, this exponential growth in volume, variety and velocity of data (3Vs of Big Data) offers extraordinary opportunity to trigger growth with new products and services.

Many players in the financial vertical, though wary at the start, have become enthusiastic adopters of big data technologies such as Hadoop.

Banks and financial companies are using innovative technologies to consolidate data that lies in different silos, department and regions, to analyze them holistically and derive enterprise-level analytics.

Those institutions that had employed relational database management systems found it challenging to process and analyze growing amount of data and have since moved to network of data stores to solve this problem.

Based on the early adopters, here are some broad developing trends in the area of big data, particularly for the financial vertical.

Bigger and better the data set, accurate the prediction – Data collected with greater granularity over longer period of time from diverse sources, make for better predictive models and forecasts.
Better predictive models, particularly the ones related to customer behaviour leading to launch of innovative products/services that have increased conversion rates.
Reduction in cost of doing business, if Operations can use data to understand how customers do business with them.
Predict non-performance of assets by analysing payment pattern, prioritize collection and reduce chance of non-collection.

Big data is driving innovation in today’s financial services market particularly in the area of capital management, regulatory compliance, corporate performance, trade execution, security, fraud management, and other instrumental disciplines. It is particularly so in uncertain times, companies that flourish are the ones that employ statistical modeling, and predictive analytics for real-time decision making.

Business Intelligence and Business Analytics, how are they different?

Many Business Intelligence marketers have been moving onto the term “Business Analytics” but users are confused what exactly is Business Analytics and how does it differ from Business Intelligence.

My search took me to this blog by Justin Heinze, “Business Intelligence vs. Business Analytics: What’s The Difference?” out of the seven expert definitions, I liked the following three differentiations,

Pat Roche, VP – Engineering, Noetix Products, Magnitude Software, explains “Business Intelligence is needed to run the business while Business Analytics are needed to change the business.”

“…Business Intelligence is looking in the rear-view mirror and …Business Analytics is looking in front of you to see what is going to happen. This (Analytics) will help you anticipate in what’s coming, while BI will tell you what happened.”, says Mark van Rijmenam, CEO / Founder, BigData-Startups

Francois Ajenstat, Senior Director, Product Management, Tableau, puts it rather clearly when he says, “Traditional business intelligence (BI) has been focused mostly on reporting. In this approach to BI, highly-formatted reports are created by a few people—typically report developers—and distributed to an entire department or organization. More recently, the trend in analytics has been instead to provide the people who have questions about their data with the tools to get their own answers. It’s now about letting business people become analysts themselves.”

But experts are clearly divided as to whether Business Intelligence is a subset of Business Analytics or the other way round.

Timo Elliot, Innovation Evangelist, SAP, says “…when SAP says “business analytics” instead of “business intelligence”, it’s intended to indicate that business analytics is an umbrella term including data warehousing, business intelligence, enterprise information management” where as Dr. Rado Kotorov, Chief Innovation Officer of Information Builders, says “Analytics is a function of BI, BI used to refer to platform capabilities to access data, manage metadata, development tools for reports, dashboards, and applications, and publishing, scheduling and distribution capabilities. Analytics referred to either methods of analyzing information (i.e., descriptive, predictive, regression, neural networks, etc.) or the tools to perform those methods. Thus, analytics is a subset of the broader platform capabilities.”

So where do we stand, we fall back on the original definition of the word “analytics” as described in Wikipedia, “Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.”

And “Intelligence” gives “the cognitive abilities to learn, form concepts, understand, and reason, including the capacities to recognize patterns, comprehend ideas, plan, problem solve, and use language to communicate.”

So, Business Intelligence offers dashboards/reports recording trends/patterns of the data at hand while Business Analytics offers Data Discovery/Analysis tools to ask intelligent questions and get intelligent answers, the quality of the data, the tool and the intelligence of the user defines the output.

Comparing how security experts and non-experts stay safe online

A recent Google security research (beware: good read but VERY detailed) analyzed the differences in the security practices of “non-experts” and “experts” in the field of information security. The paper outlines the results of two surveys—one with 231 security experts, and another with 294 web-users who aren’t security experts—in which Google researchers asked both groups what they do to stay safe online. They wanted to compare and contrast responses from the two groups, and better understand differences and why they may exist.

The key takeaways are:

“[...]
Here are experts’ and non-experts’ top security practices, according to our study. We asked each participant to list 3 practices (see picture) The common ground: careful password management.

Clearly, careful password management is a priority for both groups. But, they differ on their approaches.

Security experts rely heavily on password managers, services that store and protect all of a user’s passwords in one place. Experts reported using password managers, for at least some of their accounts, three-times more frequently than non-experts. As one expert said, “Password managers change the whole calculus because they make it possible to have both strong and unique passwords.”

On the other hand, only 24% of non-experts reported using password managers for at least some of their accounts, compared to 73% of experts. Our findings suggested this was due to lack of education about the benefits of password managers and/or a perceived lack of trust in these programs. “I try to remember my passwords because no one can hack my mind,” one non-expert told us.

Key differences: software updates and antivirus software

Despite some overlap, experts’ and non-experts’ top answers were remarkably different.
35% of experts and only 2% of non-experts said that installing software updates was one of their top security practices. Experts recognize the benefits of updates—“Patch, patch, patch,” said one expert—while non-experts not only aren’t clear on them, but are concerned about the potential risks of software updates. A non-expert told us: “I don’t know if updating software is always safe. What [if] you download malicious software?” and “Automatic software updates are not safe in my opinion, since it can be abused to update malicious content.”
Meanwhile, 42% of non-experts vs. only 7% of experts said that running antivirus software was one of the top three three things they do to stay safe online. Experts acknowledged the benefits of antivirus software, but expressed concern that it might give users a false sense of security since it’s not a bulletproof solution.

More broadly, our findings highlight fundamental misunderstandings about basic online security practices. Software updates, for example, are the seat belts of online security; they make you safer, period. And yet, many non-experts not only overlook these as a best practice, but also mistakenly worry that software updates are a security risk.
No practice on either list—expert or non-expert—makes users less secure. But, there is clearly room to improve how security best practices are prioritized and communicated to the vast majority of (non expert) users. We’re looking forward to tackling that challenge. [...]“

Are BI Dashboards only for Big Business?

Like me, have you always thought, to have any meaningful business intelligence dashboard your company should be moderately big (in terms of data generation)? Here is an article which argues for BI dashboards for small business, pretty effectively. “Why Small Businesses Need A Business Intelligence Dashboard” (link - http://cloudtweaks.com/2015/06/small-business-intelligence-dashboard/)

The article goes on to say BI dashboards for small business offers 5 advantages,

Greater transparency - Using a BI Dashboard would provide the owner the power of real-time information of what is working and what is not, a campaign, an offer or a banner ad. He can take corrective action instantly, cutting his losses or investing more on what’s working.

Saves time - Actionable intelligence one gets out of a BI Dashboard that too instantly is what makes it valuable, the same would have needed a person to plow for half a day. Also, the information can be viewed dynamically.

Better results - It keeps you focused, you concentrate on the KPIs without the distraction of volumes of information that gets created by all departments.

Decreased stress - You as a business owner won’t be chasing the reports anymore, on the other hand, BI dashboards can update daily with key KPIs. With all important info at your fingertips, you are stress-free.

Increased productivity - This can be both ways, to increase your employee productivity as well as your’s, your productivity would go up as you are no longer looking for information to work with, that’s already available. Let’s say, one of the KPIs you are measuring is the response time in calling the leads, if you can show, earlier the prospect is called greater the chance of conversion, the productivity of your calling team would have increased drastically.

I leave it here, read the complete article for more details.

Big Data Infographics that you would like

Information graphics or infographics represents Data/Information in a visual form that helps in processing that infomation quickly and clearly however complex the data may be.

Two such Big Data infographics that caught my eye while I was going through this article – “Top Big Data Infographics From The Past Year” (http://businessintelligence.com/bi-insights/top-big-data-infographics-from-the-past-year/) are here below.

The first one, “The who, why and how of Big Data”,(http://www.bain.com/infographics/big-data/), has a representation that comes as no surprise as to who would be the largest spender for Big Data services, you guesses are right, Financial services companies followed by Software/Internet and Government, in the current year these verticals will be spending $6.4 bn and 2.8 bn respectively.

Then the third visual on the same infographic speaks about the model in which companies would “make Big Data part of their operations…”, what really interested me was the line “But none of them are led by IT”. That comes as no surprise to a few but is still surprising for many as even a year ago most (almost 40% according to one survey) of the Big Data effort were led by IT departments.

The second infographic, “How much data does the world create every year?” (https://web-assets.domo.com/blog/wp-content/uploads/2013/05/ThePhysicalSizeofBigData.jpg) would make your mind go numb. They quote a report from Stanford Univ. which says, the whole of humanity produces around 1200 Exabytes of data every year.

Got lost, just like me, the infographic puts it in perspective in more than couple of ways, here is one.

1200 Exabytes, when broken into GBs and stored on a common device, say 16 GB iPhone 5s, would take 80.53 billion phones, that is like, placing these phones next to each other would cover 100 circles around the earth.

Simply amazing, isn’t it?