Interactive Analysis and Related Tools - Part II

In my last article, I have talk about interactive analysis from the definition and explains with an example, and today we will discuss the characteristics of interactive analytics.

As we can see from the above examples, the real world business data analysis is far more complex than the theory. The commercial opportunity changes unpredictably and comes and goes in a moment of doze. In fact, the computation on the business activities is usually fuzzy. There are few model algorithms from textbook that can be used to solve the real business situation. The interactive analysis computation is to solve the problem in the real world. Business intelligence tools should be more simple, and most importantly, interactive analysis should be simplied. Let’s check the characteristics of interactive analysis.

Fixed algorithm as bottom layer

Interactive analysis can be always resolved to the fixed algorithm. For example, ranking algorithm is usually used to compute the “Appearance of Large Order”; grouping algorithm is usually used to compute the “which sector sees the intensive procurement by clients”.

Focus on the interactive procedure

The bottom layer of interactive analysis is the fixed algorithm though, the human intervention is necessary. How to break down the target? How to set the priority of branches? Whether to carry on the mining or not? Is the existing result enough to support the decision-making? Is the further computation necessary? Theoretically speaking, the power enough computer programs can implement the above network-like branches, and thus turn it into the fixed algorithm. However, before the The Matrix and Neo born, the analyzers will have to take great effort in it.

Focus on the business expert

Interactive analysis is to solve the problem in the real world. The assumption will have to make on the basis of business status, and the next step computation will be decided on the current data and business experiences. To do this, the abundant business knowledge is required. The qualified analyzer is usually the business expert. The database administer and programmer are more fit to seek the solutions to the fixed algorithm and they are able to provide the assistance in computation but hard to make the most important business decision.

Take massive structured data as the primary goal

The massive structured data is the data capable to be represented with a 2-dimention structure. Of the massive structural data, the typical examples are the data from database and spreadsheet, and text file. In the business activities of real world, these data are the most common and fundamental, acting as the base of business calculation.

This is the End of Part II for interactive analysis. In the next part, I will talk about the related tools for interactive analysis.

To be continued…

Related Reading

Interactive Analysis and Related Tools - Part I

Interactive Analysis and Related Tools - Part I

From today, I will talk something about interactive analytics and a series of related tools in business intelligence industry. For those who doesn’t know much about interactive analysis and its tools, I wish my articles are helpful to you. I will explain interactive analytics from its definition and with case examples to help you understand today.

Definition

Interactive analysis is a cycle analysis procedure of assumption, validation, and adjustment to achieve the fuzzy computation goal.

The interactive analysis is the real on-line analysis to solve the complex computation problem in the real world, and it is one of the key points in the business computation.

Example of Case

Let us explain the interactive analysis with a common example in the business activities.

Step 1 Set the goal

Why the sales volume this month greatly exceeds that of the previous month?

Obviously, this is a fuzzy computation goal with several possible answers. You cannot get the result directly using any analysis mode.

Step 2 Guess the possible branch

Since there are several possibilities to give rise to the sales volume increase, the analyzer has to check every possibility, such as:

l         Orders numbers increase

l         Appearance of large orders

l         Intensive consumption of specific customer base, for example the intensive screening the movies of children in the summer holiday

l         Improvement of process

l         Launching a marketing campaign

…...

Obviously, a certain level of business knowledge is required to make these assumptions and the keen sense of smell to the circumstances inside and outside the enterprise. This is a relatively personalized effort.

Step 3 Branch validation

Based on the possibility and characteristics of data, the analyzer will choose a branch to start the analysis, such as Increase of Orders. If the number of orders does not increase through the calculating for validation, then it indicates that this assumption is not correct. You need to validate the next assumption to carry on the cyclic analysis.

For example, by going through the validation on this branch of Appearance of Large Order, the analyzer finds this is correct, and thus this branch can be justified.

Step 4 In-depth exploration and mining

These possibilities are usually the apparent cause instead of the root cause. To really settle the problem, you will have to drill down step by step to reach the core. For example, the appearance of large order may result from:

l         The new salesmen is highly capable

l         The new sales policy of the company boosts the large order

l         Intensive procurement of clients from a certain sector

…...

It is obvious that the process of drill-down is a cyclic procedure. The analyzer must judge on the characteristics of data at that specific point to choose the branch of the highest possibility, so as to progress level by level, until the problem is solved.

Step 5 Solve problem

The procedure of exploration and mining does not require the unlimited drilling down. The whole procedure can put an end once a clear answer enough to make a decision is found. For example, through the validation, the Centralized Procurement in a Certain Sector is determined just the root cause. Then, this is enough for analyzer to make a decision: The sales volume can keep rising by simply beefing up the sales forces and efforts in this sector since the recent sales rise is the result of centralized procurement by the clients in this sector. 

Step 6  More computations

To this step, the computation goal is achieved. However, we can realize more business values through more computation on the basis of the existing results, such as:

l         Find the list of customers in this sector

l         Find the list of salesman which are good at this sector

l         Find the reason why the client in this sector increase the procurement quantities abruptly

l         Find the abnormal actions in the sector related to this sector and the downstream/upstream sector.

And this is the end of first part for Interactive Analysis and Related Tools. 

Thanks everyone for reading and providing comments. If you have any questions, please let me know. Your feedback is valued and appreciated by we Raqsoft!
To be continued...

Related Readings:
Interactive Analysis and Related Tools - Part II
Interactive Analysis and Related Tools - Part III