Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Interactive Analytics and OLAP – Part II
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Predictive Analytics > Interactive Analytics and OLAP – Part II
AnalyticsPredictive Analytics

Interactive Analytics and OLAP – Part II

raqsoft
raqsoft
0 Min Read
SHARE

After the first stage of real application process of the OLAP in interactive analytics and OLAP – Part I, we will start OLAP application of stage 2. 

After the first stage of real application process of the OLAP in interactive analytics and OLAP – Part I, we will start OLAP application of stage 2. 

Those guesses in part I of interactive data analytics are just the basis for forecast. After operating for a period of time, a constructed business system can also accumulate large quantities of data (so called complex data calculation), and these guesses have most probably been evaluated by these accumulated data, when evaluated to be true, they can be used in forecast; when evaluated to be false they will be re-guessed.

 It needs to be noted that these guesses are made by users themselves instead of the computer system! Instant data analytics is started by human being in OLAP. What a computer should do is to help a user to evaluate according to the existing data, the guess to be true or false, namely, on-line data query (including certain aggregation computation). This is just the application process of OLAP. The reason why on-line analysis is needed is that many query computations are temporarily required after a user has seen a certain intermediate result. In the whole process, model in advance is impossible and unnecessary (Raqsoft esProc is born to deal with these issues).

More Read

predictive analytics in dropshipping
Predictive Analytics Helps New Dropshipping Businesses Thrive
Putting predictive analytics to work with decision management #paw
BI Shouldn’t Be Part-time Pursuit for Analysts
Here’s how to prevent mistakes in analytic projects with decision management
Successful Business Intelligence Projects: The Role of Managers and Leaders

We call the above process evaluation process, whose purpose is to find from historical data some laws or evidences for conclusions, and the means adopted is to conduct interactive query computation on historical data. And this process can be a complex data calculation.

  •        The following are a few examples actually requiring computations (or queries):
  •        The first n customers whose purchases from the company account for half of the sales volume of the company of the current year;
  •        The stocks which go up to the limit for three consecutive days within one month;
  •        Commodities in the supermarket which are sold out at 5 P.M for three times within one month;
  •        Commodities whose sales volumes in this month have decreased by more than 20% over those of the preceding month;

       …

Evidently, this type of computation demand is ubiquitous in business analysis process and all can be computed out from historical database.

Then, can the narrowed OLAP be used to complete the above-mentioned data computation process?

In the third part of Interactive Analytics and OLAP, i will answer the question above.

Sponsored by http://www.raqsoft.com

To be continued… 

Related Articles:

Interactive Analytics and OLAP – Part I

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Diverse Research Datasets
The 5 Best Platforms Offering the Most Diverse Research Datasets in 2026
Big Data Exclusive
macro intelligence and ai
How Permutable AI is Advancing Macro Intelligence for Complex Global Markets
Artificial Intelligence Exclusive
warehouse accidents
Data Analytics and the Future of Warehouse Safety
Analytics Commentary Exclusive
stock investing and data analytics
How Data Analytics Supports Smarter Stock Trading Strategies
Analytics Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Cloud Computing Lingo

6 Min Read
data analytics insurance
Analytics

Small Companies Use Analytics to Save Big On Business Insurance

7 Min Read

How NOAA uses R to forecast river flooding.

2 Min Read

Workplace Ups and Downs

2 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?