Simplifying big data may be useful, but only to a certain extent
As foreseen in “tempore non suspecto”, big data are more and more often used as a fundamental ( even crucial ) part of analysis and marketing processes. Despite their obvious usefulness, however, few decision‐makers can actually read, understand, match and translate them into trends which may be turned into real developments. A possible solution to such stalemate situation could be finding a system aimed at simplifying the life of those processing big data. With this regard, a solution called ClearGraph clearly stands out among competitors. Designed by a start‐up based in Palo Alto, recently taken over by Tableau Software, it is a ‘data discovery’ technology, using a natural language for searches. Basically, ClearGraph simplifies the process of working with big data because, thanks to it, you don’t need to be a coding expert to get some clear answers from big data, for instance knowing the language used by Sql database, or knowing why data are collected as maps, pie charts, bar graphs and diagrams, in response to a given query entered as usually uttered vocally by common humans, which means sometimes ambiguously or imprecisely. Read it in Italian.
Just to provide you with an insight on what Adrian Bridgwater suggested on Forbes about this topic, if you ask an IT system the price of BMW cars on sale in Lombardy, the logic answer will include all possible answers concerning new cars, second‐hand cars, those with a certain amount of km, a given color or optionals, etc… . Which means that the query entered is too unspecific and, even trying to add more details, such as BMW on sale in Lombardy within an area of 100km from our current position, with a price under 30 thousand Euros, excluding the grey ones, we would still be lacking some information which are crucial for the generation of an outcome which may be of any use to us (Now You Can ‘Talk’ To A Database, Tableau Acquires ClearGraph.
And that is where ClearGraph may come in handy: access to such data and their analysis carried out through the software doesn’t require any type of technical training, since the system can infer the user’s intention thanks to its machine learning technology and using the same semantics used by bots for chats used by social networks. In other words it uses a sort of “conversational ” language. Thus, anyone can ask for the total sales figures concerning BMW cars in Lombardy and then focus only on orders places within the past 30 days in Milan, and then continue to group data more and more specifically (in a more useful way).
Such query based on a natural language records semantic data contained in the charts and learns over time. To the point it can suggest the metrics which are worth being monitored, and highlight the trends to be taken into consideration.
The feedback from Tableau Software customers has been absolutely positive, so far (Tableau Software CEO explains how ClearGraph acquisition will further)
The reason of this is clear: thanks to such system, big data can now be handled even by people who don’t know anything about statistics.
Nevertheless, believing experts have got useless would be a mistake. Getting all the database belonging to a company divisions integrated in just one system and having some visual interactive maps to be used by managers who are not knowledgeable about data is an obvious advantage, but the risk of simplifying data too much is analysis are too simplified, as well! So, go and have your life simplified by the new software but do it wisely.
What do you think about the fact of simplifying big data analysis to the benefit of the common people? Tweet @agostinellialdo.
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