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If you want better analytics, here are 7 reasons to ditch data cubes…

In our previous article, the BI technology battle has already been fought… and won, we discussed the existence of data bloat, the 2 approaches to dealing with it, and the fact that the Associative approach (as championed by Business Intelligence market leader Qlik – and kind of/sort of copycatted by Microsoft and SAP) has thoroughly gained the ascendency over the outdated Cube approach.

The 7 real-world, day-to-day, speed-to-value reasons to adopt Qlik’s Associative approach are that:

1. Any field can be used to filter any other field.
There is no need to define dimensions or measures in the data store. This eliminates a layer of costly data architectural overhead immediately.

2. A universal search across all data is easily performed.
For example, you remember that the record you are looking for contained the number “230” somewhere in it. You can search for all records that contain “230” via the universal search bar. This will reveal those records that contain 230 within them e.g.

i)   Sales amounts e.g. 230.66; 2,3092; 23,095; 14,230.88 etc.;
ii)  Product SKU e.g. HTTJ2305567;
iii) Postal codes;
iv) Latitude or longitude; and
v)  Long form comments…etc. etc. etc.

3. The non-techie end user can see what people are not doing i.e. you can see the reverse of your query at the same time as your query.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1552876976895{padding-top: 3% !important;padding-bottom: 3% !important;}”][vc_column][vc_single_image image=”27571″ img_size=”full” alignment=”center” css=”.vc_custom_1552880576142{padding-bottom: 4% !important;}”][/vc_column][/vc_row][vc_row][vc_column][vc_column_text]In the graphic above, data selected or filtered upon is green, data that is associated with that selection is white, data that could have been selected with this combination of selections is light grey and data that is not associated with the selections at all is dark grey (it is the reverse of the selections). With this technology, you can see which of your customers has bought product A, but not its companion product B in one click allowing you to immediately target those customers with a companion product offer. Standard, Cube or row-based tools cannot do this without cutting a new complex query every time.

This fact alone creates unbeatable speed-to-value advantages over Cubes that cannot be overstated.

4. You can pull in low-lying transactional data to reveal patterns that would otherwise be lost in the Cube summary process.
Your data is fully responsive and you don’t have to wait for IT to build a new Cube every time you want to ask a new question.

5. Associative has a much smaller hardware footprint while producing superior results. The Associative model drastically reduces the need for storage and throughput hardware, saving you money.

6. It is the foundation and benchmark for superfast “in-memory” computing which delivers answers to questions far more quickly than traditional reporting methods.
No-one likes clicking on a report and then watching a spinning icon while data is pulled from disk storage. Take this frustration and times it by 100 for those tasked with the daily job of analysing information from multiple different perspectives.

[/vc_column_text][vc_single_image image=”27562″ img_size=”full” alignment=”center” css=”.vc_custom_1552880540432{padding-bottom: 4% !important;}”][vc_column_text]Qlik’s response to this frustration was to build and optimise its in-memory associative engine back in the 1990s when RAM was the most expensive part of a computer. With a 20-year head start on the market, in-memory operation is completely intrinsic to the way Qlik operates.

7. Projects are measured in days and weeks rather than months and years.
Qlik’s fundamental Associative architecture means that projects are agile by default. As a result, organisations can build, consume, analyse and pivot data apps in a matter of days, rather than the months and years seen with Cube-based projects.

Qlik is a purpose built, in-memory, Associative BI tool created from the ground up on a technology stack. This allows the untrained, non-techie user to easily trawl through data, pivoting from question to question as quickly (or slowly) as they like.

Next time someone tells you that they have this fantastic BI product that uses some form of data Cubes, remember that the battle between Cubes Vs. Associative has been fought and won with Associative the clear winner.

Then when they tell you that their cubes are different and that their performance mimics the best in-memory products out there, remember that despite the headlong rush of SAP and Microsoft to create “Associative-ish” copy-cat engines, the reality is that Qlik’s underlying and patented Associative technology story remains completely unrivalled.

Finally, if you are at the end of your decision-making process for a BI tool and Qlik is in the frame (as it absolutely should be), ask yourself this question:

“Why would I bet against a company that has a 20-year, patented head start in the development and optimisation of the only Associative engine in the BI market place?”

If you would like to speak to me or any of our consultants about the advantages of choosing Associative for your organisation, please get in touch.

Read the previous companion article The BI technology battle has already been fought… and won.

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Richard Blakemore
Practice Leader
ABM Systems

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