Monday, July 11, 2016

BI Framework

In today’s fast-paced business world, it is imperative for the Top executives to have the insight and data they need in order to make the right calls. Business Intelligence is the key to making those correct decisions, as it joins data, technology, analytics, and knowledge to help business professionals make the optimal decisions that drive their enterprise’s success. 
In our   day-to-day operations Data is generated from various streams like social media (YouTube, Twitter, Facebook), Mobile phones, smart watches, smart TV’s, online e-commerce portals like Amazon etc. It shows that internet population has risen globally by more than 60% and there is more usage of mobile devices by the people.

Most businesses have the ability to capture data from customer transactions and day-to-day operations, and through research. However, the significant problem after accumulating data is how to turn the data into intelligence. The solution to streamlining the data-analyzing processes involves in deeper knowledge on Business Intelligence, which makes it possible to analyze and share information very quickly and collaboratively. 


How Business Analytics model works?
There are certain skills that is required to develop and build analytic models. There are steps to followed at each process level:
·         Define the Problem
Ø  Knowledge on how the business works
Ø  Find answers to the questions – Who, when, what and where?
·         Get the data
Ø  Data Acquisition
Ø  Data profiling
Ø  Data Quality assessment
·         Prepare the data
Ø  Data cleansing and quality improvement
Ø  Data Sampling
Ø  Data Structures, migration
·         Choose the modeling technique
Ø  Knowledge on statistical methods
·         Build the model
Ø  Define the purpose of the model
Ø  Structure the model – Spreadsheets, visualizations etc.
·         Evaluate the model
Ø  Model testing with test cases
Ø  Precision, accuracy, reliability
·         Deploy the model
Ø  Production implementation for execution
Ø  Change monitoring and model maintenance

Modules in BI

·         Dashboards
BI dashboards can provide customers a snapshot of daily operations and helps in monitoring activities that assist the user in identifying problems and the source of those problems. It provides up to date info on financial results, sales and their critical info.
·         KPI (Key Performance Indicators)
KPI management helps in tracking with powerful features, formulae and expressions, and flexible frequency and threshold levels. It gives concise definition and tracking of performance indicators for a period, and measures performance as compared to previous period.
·         Graphical OLAP
Graphical Business Intelligence(BI) OLAP technology makes it easy for the uses to find, filter and analyze data going beyond numbers and allowing users to visualize the information with eye-catching, stunning displays, valuable indicators and gauges.
·         Forecasting
Our Predictive analysis uses historical product, sales, pricing, financial, budget and other data and forecasts the measures with numerous time series. Options, e.g., Year, quarter, month, week, day, hour or even second to improve your planning process.
·         Graphical Reporting
BI reports delivers web based BI reports to anyone in the organization. It is simple to use, practical to implement and affordable for every organization. With this we can create a report to summarize your performance metrics and operational data.

How BI is effectively used in smartphones?
There are 6 factors to be considered to make mobile BI successful. Or when an enterprise tries to enhance mobile capabilities to it.
1.       An app’s purpose
Take time up front to map your standard BI processes and queries to the groups of employees that most frequently use them, and then make those functions easily accessible – thumb-size onscreen buttons work best, if possible. That way, all employees don’t have to scroll through long lists or click through multiple links to initiate BI tasks.
2.       Development models
BI can be built as native app, meaning the app is completely device- and platform-specific: one version for Android, another for iOS, plus any other platforms. It can be deployed as a mobile web app, a web-based app that runs entirely on your servers and is accessed via a mobile browser using HTML5.
3.       Connectivity
Even with today’s speediest networks, it’s tough to give mobile users true interactive data exploration. Downloading large data sets takes too much time, and visualizing data of any great volume can choke even the most powerful mobile devices.
4.       Security
BI systems hold some of your company’s most valuable data, so CSOs worry about making that data accessible via hundreds or thousands of pocket-sized, lo-sable, steal able devices.
5.       Device Features: Mobile devices enable your users to do more than just consume information.
With a camera, GPS, and other features, mobiles can also feed data into your BI systems. The camera can scan bar codes (or faces), and the GPS can help users locate nearby resources, both human and physical. Look at where your BI processes collect data – or where you wish you had more data – and see if you can leverage your employees’ mobile devices to collect it.
6.       Feedback
Track who’s using your mobile BI apps and learn from what they do. You can automate some of this process, but it’s also important to actually talk with users to hear their frustrations and success stories, collect their suggestions, and ask about new features you’re considering. That’s why your chosen development model is important.

Conclusion:
There are some top IT investors, CIO’s of big organizations are predicting good reviews about the future of BI. Cloud services, Predictive analytics, Big data each plays a substantial role in feeding data to the BI systems. Business intelligence (BI) sits at the center of many organizations’ efforts to enable data-driven decisions and actions through their enterprises. Some suggests that BI will become personalized that means reports are developed once and used by many today simply because too many technical resources are required to personalize them. The hard limits of a "report" will fade away and be replaced by personalized data presentations showing the data you like to see in the format you like to see it in.

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