Defining terms – Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making. Predictive analytics encompasses a variety of techniques from statistics, data mining and game theory that analyze current and historical facts to make predictions about future events.

Business intelligence provides valuable insight into the state of affairs within an organization. The information is critical to decision-making. But when combined with predictive analysis, synergies can be leveraged to improve business and operations.

The easy analogy between BI and predictive analysis can be described as follows. A good rugby player plays where the ball is, a great rugby player plays where the ball is going to be.

BI tools help users know what has happened and what is happening, while predictive analytics tools

Help to elicit more from this information by providing an understanding of why these things happened and in predicting what will happen.

 For example, BI tools can report which sales region had the highest sales, how many widgets were sold in stores in different ZIP codes, the average spending per online customer vs. in-store customer, and how many customers stopped doing business with your company last year. All of this information is essential for developing new product and services, allocating resources, investing in marketing

campaigns, and so on.

  Predictive analytics tools, though, can give deeper insight into why these things happened. For example, knowing the average customer spends $100 per visit to a store is one thing. Knowing that a certain 20 percent of the customers are responsible for 80 percent of all revenues and that they are more likely to buy particular products bundled together is much more valuable. Also, identifying which products influenced the purchase of others or the strength of the relationship between products purchased together would give more insight into specific buying patterns.

  This added level of analysis can yield valuable results. It helps you understand how that prized segment of your customer base would respond to very targeted promotions.

 Predictive analytics helps organizations look forward and make educated decisions that anticipate the future needs of customers. It combines known information about customers, sales, operations, or finances, with critical insight that helps solve problems, achieve business objectives, and uncover hidden patterns not easily identifiable through reports or dashboards. The combined knowledge is used to take actions that can improve business.

Everyone is going on about cloud computing, what is it and should you be considering it?

From what I have read and now come to understand, not fully I must add, cloud computing is a computing model not a technology. In this model of computing, all the servers, networks, applications and other elements related to data centers are made available to IT and end users via the Internet.

And I always thought cl;oud computing was for software only, but I was wrong. There appear to be  different types of cloud computing; Platform as a Service, Infrastructure as a Service and Software as a Service.

Before you consider Cloud computing you should probably consider a few things:

• what are the viable paths to move legacy systems to the cloud?
• are there architectual changes that need to happen between cloud and non cloud applications?
• Will the cloud computing change current technology and operational process?
• Do you go with a private cloud or a public/ hosted cloud?
• And I guess for some countries around the world, will your bandwidth allow for fast and flexible cloud computing?

My head is in the Clouds

What can the product do? How does it meet our requirements?

If you clearly define your business requirements before meeting with a BI vendor, aligning their product with your organization’s needs will be a much smoother process.

 What pricing/licensing options are available?

Many vendors offer multiple licensing styles. A few of the most popular options are:

• Concurrent users
• Role based
• Server based
• Web based

How will your BI software integrate into our current environment?

If you have outlined the technical requirements — source systems, databases, hardware platforms, etc. — it will be easier for the vendor to discuss the integration process with you.

Will we be able to test the product in our environment? Can we get a proof of concept?

How are support and maintenance contracts set up?

If you are using a new vendor and a new product, it’s likely that your users and administrators are going to need technical support – particularly during the first year of implementation. Ask vendors for specifics and detailed pricing for support, training and maintenance.

 How long will implementation take? Will we need consultants or vendor services?

Make sure the implementation time frame given by the vendor is realistic, experts warn, and matches the time frame you have determined for yourself. There are often vendor services teams or independent consultants that can assist you — either throughout the whole process or for specific decisions/questions.

 What are your software update cycles like? How easy is it to add on new functions/features?

When your reporting requirements change at some point down the road, your BI software may have to change, too. Make sure you talk with the vendor about the process and cost of adding on new features at a later date.

Can I talk to one of your customers in an industry similar to mine?

The best insight into vendors and products comes from people with firsthand experience, all experts agreed. Ask your vendor whether you can talk to one of their customers, ideally a similarly sized organization with similar needs.

“Talk to people in the same industry, with similar types of applications, similar types of users — that’s where the real value comes in,”