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Analysis has been with us since the dawn of human consciousness. When early man tried to understand why an animal drops when you hit it with a rock, he made the first analysis.
Analysis means nothing more than breaking down an action or event into its individual parts in order to understand it better.
Today's world is to a great extent run by computers. With it, analysis morphed into a complex and sophisticated discipline that looks at data and data streams to discover inherent patterns. This is called analytics. It uses science and computer technology to find, track and gather data to analyze and interpret. Analytical probing can become the basis for predictive analytics.
If you own a website, a blog, an email or social media account you see ads. They are ubiquitous and often annoying. Ever wondered why you suddenly are bombarded with ads for automobiles as soon tell a friend on Facebook that you are looking for a new car?
You just have met custom analytics applications. Google analytics to be specific. We also refer to it often by the generic term 'data mining.'
However, Google is only one of the most visible incarnations of a specific type of analytics. There are many more categories of custom analytics. Together they spawned an entire interdisciplinary industry that delivers this type of comprehensive analytics. Forio is a company that specializes in developing custom analytics applications for their customers.
Who uses analytics applications?
The simple answer would be, companies that do big business with other businesses or with consumers. These types of companies routinely have a big data flow as a total and in individual departments of the business. Among them are, retail sales, inventory control, sales by product or service, results of marketing decisions, the performance of the sales force, price optimization, financing and credit, loss prevention, lists of best-selling items and predictions of trends for future sales. Of course, many other companies and business or administrative entities can and do benefit from a custom analytics application.
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Custom analytics also has a place in government, non-profit organizations and even in science. There it takes the form of predictive analytics. Scientists often use existing data to build scenarios that allow them to predict situations that will exist in still unexplored events and areas.
Who provides analytics applications?
A custom analytics application is a very intricate and advanced pieces of software. They frequently involve the expertise of specialists from many fields of business, science and government. The quality of the work of a company that develops analytics software depends on the quality of its team of experts. More is not always better. But a custom analytics application requires the cooperation of more outstanding experts than most other software developers.
Customized analytics applications involve almost invariably extensive computerized data processing. Members of custom analytics must, therefore, be familiar and comfortable with the most current techniques used in computer science and statistics. And let us not forget mathematics.
The best developers of analytics applications have on staff teams of highly qualified experts in these fields. They also have access to a network of qualified, experienced specialists from other disciplines when the need arises.
What can a custom analytics application do for you?
That depends almost entirely on the needs of your business. A customized analytics application will do whatever you want, within reason, of course.
The first step in the process of developing an application is to discuss the needs of a potential customer and to review existing analytics software in use, if any. This is the entry point for ideas to improve the analytics. Next, the developers will create a sample or mockup test application for the potential customer.
Developing an interactive analytics application is the main step in the process. That's where all the heavy lifting by the assembled team of experts is done before the results are presented to the potential customer. When the customer approves the concept, an extensive test phase will follow. During this phase, the new analytics application is deployed and tested. These tests expose the new analytics software to various browsers and computing devices. During this phase, testing explores potential compatibility issues between the analytics application and other software, browsers, and device related operating software.
The final product will be a professionally looking custom analytics application with state of the art modeling; and, hopefully, with equally comprehensive customer support and care.
Many, if not all, developers of analytics applications have a number of stock packaged applications available. They cover the most common scenarios and uses. In addition, these package applications can form the basis for a custom analytics application. Smaller companies with less complex analytics needs find them a good alternative to fully customized software.
Several companies make the most basic packages the center of their customer service and support services. Customers can subscribe to the software on a monthly or annual basis. Subscription prices are surprisingly reasonable.
Examples of such packages include a route optimizer (not only for salespeople), a restaurant finder that uses your past preferences to find new places to eat, a public health organizer and an investment planner.
And The Future Of Custom Analytics Applications?
Custom analytics is not going away. On the contrary, they will be with us for a very long time. Businesses, educational organizations, governments and close to anyone else under the sun will use one of these applications and simulations in one form or another.
Data storage is getting ever cheaper. Terabytes of storage are available at low prices. As a result, companies do not have to discard old date to save space. These data will be there for analysis with more current and more sophisticated analytics programs whenever needed.
At the same time, data processing speeds and capacities are increasing. Now, that makes it possible to crunch more data in less time.
When you add mobile analytics and the wealth of analytics materials mined on social media the inevitable conclusion is that custom analytics applications and data analysis still have a long way to go before they reach the apex.