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Behavioral Analytics is the next generation of business intelligence

admin — Mon, 04 Sep 2017 06:08:47 +0000

Writing an opinion piece in the CIO magazine, Den Steiner – adviser CIO explains how behavioral analytics is turning out to be the new hope for business leaders in their quest for cost – effective mechanisms to analyze business data to gain competitive advantage.

Beginning how today enterprises collect extensive data in course of their business transactions, Den Steiner goes on to tell us this data can be utilized to gain a competitive advantage in the market place when it is streamlined and formatted in an efficient way to lend actionable information.

But with enterprises encountering the challenges of the need for powerful architecture, robust data – warehousing and separate data visualization, this process most times lead to perplexing workflow and foggy analysis resulting in a more or less a very low efficient system.

In their bid to overcome these lacunae, business leaders tend to concentrate their resources on a single channel say mobile activity or website visitors and their page clicks to focus on activity levels and conversion rates. This even though useful to a certain extent they would have made use of a very small set of data.

Enterprises with deep pockets tend to face challenges of data sitting in different silos requiring the services of a development team to get a factual understanding of different data sets as the present data integration process is complex.

In the above scenario, the advent of behavioral analytics offers a solution which unifies the entire of digital activity, making it easy for enterprises to trace the customer’s journey from start to finish.

As is the practice, few industries are faster off the starting block in adopting behavioral analytics than others, on –line merchants in their quest technology innovation are in the fore front but many other industries like cyber – security, gaming and fin –tech can benefit equally from investing in this business intelligence.

And Den Steiner makes a strong case for enterprises to make behavior and its analysis the center in their need to organize data. And is of the firm view that behavioral analytics is the next generation business intelligence.

For more, please visit: https://www.cio.com/article/3216109/business-intelligence/here-s-why-behavioral-analytics-is-the-next-generation-of-business-intelligence.html

How machines learn?

admin — Mon, 27 Mar 2017 04:07:51 +0000

Writing in Datanami, a news portal dedicated to Big Data news, insights and analysis, Fiona McNeill, a SAS global marketer and Dr. Hui Li, senior staff scientist for SAS, shares light on how machines learn. Starting with examples of various enterprises using machine learning to design personalized offerings to attract customers, they then raise the important point of different vendors jumping on the bandwagon of machine learning with their own approaches and solutions making the whole thing confounding to the user. And thru’ this article in Datanami, the duo from SAS try to unravel machine learning and make it easier for users to understand how exactly machine learning works.

Machine learning models are designed to learn how to perform tasks and with algorithms designed to see relationships and patterns between various factors, these models learn continuously from data. And to generalize this model for business they are then validated on whole set of new data not used initially for training. These models may be made to learn in different ways like supervised learning, semi-supervised, unsupervised and reinforcement learning.

Machine learning is at the center of many advanced intelligent solutions emerging now, like AI, Neural networks, Natural Language Process and Cognitive Computing.

Artificial Intelligence – A discipline enabling the design of machine with problem solving skills to accomplish tasks just as human beings can.
Neural Networks and Deep Learning – Neural networks are programs written to learn from observational data and present solution to the problem on hand. These are used in speech and image recognition and are very successful in supervised learning.
Natural Language Processing and Cognitive Computing – NLPs are interfaces which enable machines to understand human language and humans to interpret machine output. These are applied in image captioning, text generation and machine translation.

The confluence of Big Data and massive parallel computational environments are driving the machine learning initiatives and the goal is to deliver solutions that can be highly customizable and with human – like cognition features.

For more on this, please visit: https://www.datanami.com/2017/01/31/intelligent-machines-learn-make-sense-world/

Container versus Virtual Machines – Few Basic Differences

admin — Tue, 27 Sep 2016 04:07:06 +0000

Container technology is making rapid strides with some recent reports putting the adoption rate as high as 5x times in one year. But surprisingly not many are aware of Container technology and how exactly it is different from virtual machines.

In the last decade, due to the rapid advancement in server technology the bare metal applications i.e. applications programmed to work on specific hardware in a system was unable to fully utilize the processing power and capacity of servers, leaving resources underutilized necessitating the birth of virtual machines.

Virtual machines are designed by the emulation of particular hardware system by running software on top of a physical server. Many VMs with different operating systems may be run on the same physical server with a unique OS inside each VM. So a Linux VM may easily co-exist with a Unix VM. The benefits of this technology was, it ushered in a system of consolidation of applications on to a single system instead of the prevalent single application/system accruing massive cost benefits and helping in optimal utilization of processing power and capacity of physical systems.

Container is a complete package consisting of entire runtime environment: an application, plus all its dependencies, its libraries, binaries and configuration files. This way the differences in OS distribution and the underlying infrastructure may be overcome to make the application portable on to any platform or OS.

In short, three VMs with three separate OSes running on top of it may sit on a single physical system with a hypervisor, whereas three containerized application runs on a single OS in a single server.

The size of a VM and a Container varies widely, sometime a Container may be in megabytes, the VMs because of its operation systems will usually be in gigabytes. So obviously a single server can host more containers than it can host VMs. And for this same reason a container can boot almost instantly whereas a VM may take several minutes.

But as several containers share the same OS on the kernel level, it cannot provide the same degree of isolation as a VM does and so is lot more vulnerable to security threats.

Who moved my Apps?

admin — Tue, 27 Sep 2016 03:58:48 +0000

Progressive Web Apps (PWA) are making a silent march onto users mobile with space constricting for native mobile apps.

Even with a worldwide download of 102,062m apps in 2016, is mobile web making a comeback? Probably yes, if you believe this story by BI Intelligence Apps and Platforms briefing.

Surprisingly, the foremost reason given by users for not using mobile apps is, they like using website better (53%), security concerns (31%) and too much space on the mobile (28%). Reinforcing this feeling is another study which tells, almost 20% of user’s drop-off from the stage of download to using the app.

Taking advantage of this is Google’s PWA (Progressive Web Apps) open-source initiative. Announced in 2015, PWA is a sort of hybrid of app and web page, offering look and feel of an app on web. This ensures the user immediately starts using the app instead of spending time/bandwidth on downloading and installing the app.

This might have stemmed from the fact that Google wants users to spend more of their time on mobile web than on app, even though the fact that Google receives more web searches from mobile than desktop. The fact that many apps have metamorphosed themselves into a platform has not helped Google.

So, what does this mean for business apps, most welcome this shift. Even though time spent on mobile has increased, business have conceded that there are limitations on number of brands a user can have on his mobile, so the message is “Mobile – Yes, Mobile app – No”. PWA provides a more open field for companies to displace brands and switch loyalties.

From user’s perspective, when would a user prefer a mobile app to PWA and vice-versa? An ecommerce site or an online grocery store which he uses frequently, almost daily, can be a native mobile app as compared to an airline check-in app, where the user uses it a few times a month.

So next time when companies sit to plan their mobile strategy, they would want to consider PWA rather than being limited to building just mobile apps.

SSIS DATA PROFILING

admin — Sun, 03 Apr 2016 00:02:51 +0000

SQL Server Integration Services offers a useful tool to analyze data before you bring it into your Data Warehouse. The Profile Task will store the analysis in an XML file, which you can view using the Data Profile Viewer. Before we review how to use the Profile Task, let’s take a look at the eight types of profiles that can be generated by this control.

Candidate Key Profile Request
- Use this profile to identify the columns that make up a key in your data
Column Length Distribution Profile Request
- This profile reports the distinct lengths of string values in selected columns and the percentage of rows in the table that each length represents. Use this profile to identify invalid data, for example a United States state code column with more than two characters.
Column Null Ratio Profile Request
- As the name implies, this profile will report the percentage of null values in selected columns. Use this profile to identify unexpectedly high ratios of null values.
Column Pattern Profile Request
- Reports a set of regular expressions that cover the specified percentage of values in a string column. Use this profile to identify invalid strings in your data, such as Zip Code/Postal Code that do not fit a specific format.
Column Statistics Profile Request
- Reports statistics such as minimum, maximum, average and standard deviation for numeric columns, and minimum and maximum for datetime columns. Use this profile to look for out of range values, like a column of historical dates with a maximum date in the future.
Column Value Distribution Profile Request
- This profile reports all the distinct values in selected columns and the percentage of rows in the table that each value represents. It can also report values that represent more than a specified percentage in the table. This profile can help you identify problems in your data such as an incorrect number of distinct values in a column. For example, it can tell you if you have more than 50 distinct values in a column that contains United States state codes.
Functional Dependency Profile Request
- The Functional Dependency Profile reports the extent to which the values in one column (the dependent column) depend on the values in another column or set of columns (the determinant column). This profile can also help you identify problems in your data, such as values that are not valid. For example, you profile the dependency between a column of United States Zip Codes and a column of states in the United States. The same Zip Code should always have the same state, but the profile discovers violations of this dependency.
Value Inclusion Profile Request
- The Value Inclusion Profile computes the overlap in the values between two columns or sets of columns. This profile can also determine whether a column or set of columns is appropriate to serve as a foreign key between the selected tables. This profile can also help you identify problems in your data such as values that are not valid. For example, you profile the ProductID column of a Sales table and discover that the column contains values that are not found in the ProductID column of the Products table.

SQL SERVER DATABASE ENCRYPTION STATUS

admin — Sat, 02 Apr 2016 23:54:27 +0000

Securing your data is very important and database encryption is just part of that landscape. Taking advantage SQL Server database encryption can be a daunting task but once it is configured it is also important to monitor it.

This query is intended to allow the database administrator to gain information about the status of encryption on their systems. This script can be very handy for audits or to ensure that your databases are in an a state you expect them to be in.

For those databases in your environment that require Transparent Data Encryption (TDE) this script will be invaluable for monitoring the encryption states of your databases.

SELECT
[db].name,
[db].is_encrypted,
[dek].encryption_state,
CASE [dek].encryption_state
WHEN 0 THEN 'Not Encrypted'
WHEN 1 THEN 'Unencrypted'
WHEN 2 THEN 'Encryption in progress'
WHEN 3 THEN 'Encrypted'
WHEN 4 THEN 'Key change in progress'
WHEN 5 THEN 'Decryption in progress'
WHEN 6 THEN 'Protection change in progress '
ELSE 'Not Encrypted'
END AS 'Desc'
FROM
sys.dm_database_encryption_keys [dek]
RIGHT JOIN
sys.databases [db] ON [dek].database_id = [db].database_id

Business Intelligence Tool series – Tableau, Part – 2

admin — Tue, 06 Oct 2015 05:18:50 +0000

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

admin — Mon, 05 Oct 2015 14:34:36 +0000

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

Comparing how security experts and non-experts stay safe online

admin — Thu, 30 Jul 2015 15:12:33 +0000

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. [...]“