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 Note that the Graded Discussion Board (GDB) of CS614 Data Warehousing will remain open for Two days (48 Hours only) from 12:00 AM August 9th, 2016 (Tuesday) to August 10th, 2016 (Wednesday) till 11:59 PM according to Pakistan Standard Time.

 The topic of Graded Discussion Board:

Due to the new techniques and the wide adoption of big data and its related analytical tool, old analytical methods like Online Analytical Processing (OLAP) and its different forms, may be of no use in near future. Do you agree with this statement give your opinion supported by some valid arguments you reply must not exceed the limit of 90 words or 6 lines.

 

Note: Try to provide precise (5 to 6 lines or 90 Words), to the point answer and avoid irrelevant/unnecessary details.

 

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Replies to This Discussion

Please Discuss here about this GDB.Thanks

Our main purpose here discussion not just Solution

We are here with you hands in hands to facilitate your learning and do not appreciate the idea of copying or replicating solutions.

Dear Students Don’t wait for solution post your problems here and discuss ... after discussion a perfect solution will come in a result. So, Start it now, replies here give your comments according to your knowledge and understandings....

Sir Give some idea about GDB CS614

AOA.

Kisi nay GDB kar li hai k nh?

koi to help karey ................

koi solution mila?

any idea please share

I consider these helpful answers related to our question.

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Interesting question! Part of me would like to say yes, but that definitely has to do with the fact that the companies I see are going about BI and analytics in a different way - by using data visualization and dashboards as an entry point to information access and distancing themselves from applications that are traditionally considered super user tools.

As interactivity and user friendliness become more of an integral part of BI design I think that more companies will look for different ways to perform analytics and move away from OLAP use. However, I am sure that some businesses will maintain their OLAP cubes providing their super users get benefit from them. Unfortunately, at some point, those companies will be left behind the BI technology/advancement curve.

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OLAP Cubes have a number of limitations that restrict their ability to support business decision making in today's fast-paced environment. Batch update, inflexibility, inability to apply analytics such as real-time scenario analysis, in addition to the usability issue for everyday people as Lyndsay has already pointed out. They may still have a place for strategic analysis by a super user or business analyst but businesses are increasingly looking for ways to improve execution and operational effectiveness.

A new approach is required and the capabilities enabled by real-time (or right-time) Operational BI help everyone making daily operational decisions to make better decisions more quickly - and this delivers tremendous business value.

This is the best answer Mannan on link one.

Did Big Data Kill OLAP Cubes

But my personal experience as being SAP HANA OEM Partner is that Big Data will be adjusted some where in ETL process, reason is Big data is unstructured data and OLAP comes from OLTP which is structured data. so there will be some way around in between like some hybrid solution, if we think with common sense.

CS614 GDB Solution
The topic of Graded Discussion Board: Due to the new techniques/Tecnologies and the wide adoption of big data and its related analytical tool old analytical methods like OLAP and its different forms may be of no use in near future. Do you agree with this statement give your opinion supported by some valid arguments you reply must not exceed the limit of 90 words or 6 lines. Note: Try to provide precise (5 to 6 lines or 90 Words), to the point answer and avoid irrelevant/unnecessary details.
Answer

Due to the new techniques/Tecnologies and the wide adoption of big data and its related analytical tool old analytical methods like OLAP and its different forms may be of no use in near future. Big data analytics is where advanced analytic techniques operate on big data sets. Hence, big data analytics is really about two things—big data and analytics—plus how the two have teamed up to create one of the most profound trends in business intelligence (BI) today. Let’s start by defining advanced analytics, then move on to big data and the combination of the two.
Even if you have related experience in data warehousing, reporting, and online analytic processing (OLAP), you’ll find that the business and technical requirements are different for advanced forms of analytics. To help user organizations select the right form of analytics and prepare big data for analysis, this report will discuss new options for
advanced analytics and analytic databases for big data so that users can make intelligent decisions as they embrace analytics.

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