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This blog was originally posted under: IM Blog
Back around the time that Qlik, Spotfire (TIBCO) and Tableau were first coming to prominence I researched and wrote a technical evaluation on Advizor Solutions’ offering, which is in the same BI/analytics/visualisation space as these other vendors. I liked the product a lot and ever since I have been continually surprised that when conversations turn to this space it is the first three that get mentioned and not Advizor. To my mind, it is competitive with all three of these and, in at least some respects, superior (for example, predictive modelling is built into the product, which you won’t get with, say, Tableau). So, how come it doesn’t get the attention it deserves?
The short answer in these cases is typically a matter of marketing, either the company isn’t very good at it or it lacks the funds. As it happens, Advizor recently announced data preparation capabilities (about which more later) and, as this is something I am particularly interested in right now, I took the opportunity to ask Advizor why it isn’t mentioned in the same breath as Qlik and the others, as it should be. The answer is that the company didn’t raise the sort of VC funding that its competitors did and has had to rely on organic growth rather than a large investment pot.
Sensibly, Advizor has focused on OEM arrangements and on particular market segments. In the former case, the most well-known white labelling will be by Information Builders and HP Arcsight, in the latter case for its SIEM (security information and event management) solution. With respect to the latter, the company has focused on healthcare, fundraising and manufacturing. In the case of manufacturing, especially in the mid-market. For each of these sectors, Advizor provides customisable templates (solutions) that can be licensed independently. For example, there are nine templates available for fundraisers.
Which brings me to Advizor’s data preparation. This is not self-service data preparation as you would get from companies like Paxata or Trifacta. It is instead designed, if we take manufacturing as an example, as a way to combine manufacturing shop floor data with ERP data, so that you can query and visualise data across the whole corporate environment. It is actually rather like an ETL workflow in the sense that you are collecting data from various sensors and machines on the shop floor and transforming that data in an appropriate manner so that production data can analysed along with customer order data, parts inventories and so on.
There are a number of things to say about this approach. Firstly, these transformation flows are typically built by Advizor in conjunction with the customer. This is because mid-market manufacturing organisations tend not to have the relevant IT skills or, if they do, they are busy doing other things. On the other hand I would expect that larger organisations that do have such skills could easily do this for themselves. Secondly, this puts Advizor in a good place to exploit Industry 4.0 (think the Industry of Things for manufacturing) as it develops and, thirdly, manufacturing is by no means the only environment where you want to join disparate types of data for analysis and visualisation, so I think this could have wider appeal.
To summarise, Advizor should be better known than it is. It was unfortunate that it did not get the VC funding that its competitors did but, actually, it speaks well of the company’s solution, that it has continued to grow and prosper, even if in the shadows. If you are looking at Qlik, Tableau or Spotfire you should be looking at Advizor also.