back to article Salesforce shells out $15.7bn for data viz biz Tableau

Salesforce is buying data visualisation specialist Tableau for $15.7bn as it looks to up its analytics game. As a CRM platform heavyweight, Salesforce collects caboodles of data – and the deal could make information presented by products like Customer 360 prettier to look at and maybe, just maybe, easier to understand. This …

  1. Snowy Silver badge


    Looks over priced, should have picked up one of the new startups that have been taking Tableau market share.

    1. I.Geller Bronze badge

      Re: Overpriced

      Of course overrated! They use old, n-gram parsing and don't use AI technology. Money thrown to the wind.

    2. Cederic Silver badge

      Re: Overpriced

      Who would you suggest?

      1. Gordon 10

        Re: Overpriced


    3. Anonymous Coward
      Anonymous Coward

      Re: Overpriced

      SuiteCRM? Like SugarCRM, but with all the useful bits* and some decent people doing support.

      * SugarCRM's sales model is more like selling a car for "free", but wheels, steering wheel and an engine cost extra.

    4. Morten Bjoernsvik

      Re: Overpriced

      And you can get jypyter + mathplotlib + numpy + pandas for free.

      1. Korev Silver badge

        Re: Overpriced

        That's good for analysts with Python knowledge, but Tableau, R Shiny, Spotfire etc. all provide nice visualisations for non-programmers.

  2. I.Geller Bronze badge

    n-gram parsing vs. AI-parsing.

    Well? Let's go crazy?

    So n-gram parsing vs. AI-parsing.

    In the fields of computational linguistics and probability, an n-gram is a contiguous sequence of n items from a given sample of text or speech.

    AI-parsing distills both continuous and discontinuous sequences of several words belonging to several parts of speech, a combination of a noun with other parts of speech at least one of which is a verb or an adjective.

    For example there is a sentence


    alice and bob exercise merrily, she trains a lot.


    n-gram parsing will probably not be able to recognize that "alice and bob" are names, because there are no capital letters present. Next, n-gram will get "a contiguous sequence" for the first clause (if it sees the coma) - "alice and bob exercise merrily." For the second clause - "she trains a lot". And no weights! No statistics! (Ask Larry E if you don't trust me, will you?)

    AI-parsing, using dictionary definition, detects that "alice" and "bob" are actually the names "Alice" and "Bob." After that, AI-parsing constructs two patterns for the first clause

    - Alice exercise merrily

    - Bob exercise merrily

    For the second clause AI-parsing gets also two patterns:

    - she trains a lot.

    - Alice trains a lot.

    Then AI-parsing counts weight for all patterns:

    - Alice exercise merrily - 0.25

    - Bob exercise merrily - 0.25

    - she trains a lot - 0.5

    - Alice trains a lot - 0.5

    And finally comes the index by dictionary definitions and synonyms clusters. There are three here.

    Do you see the difference? AI-parsing got four indexed by dictionary, understood by computer and weighted patterns, n-gram only two and no statistics.

    1. I.Geller Bronze badge


      How do causal relationships exist in AI ​​database? For example, a relationship between this sentence

      - alice and bob exercise merrily, she trains a lot.

      and this paragraph:

      - Alice is tired. She ran a lot, swam and trained merrily.

      In both the sentence and the paragraph there is the pattern "Alice trains(ed) a lot", which establishes a relationship.

      But the timestamp of the sentence is older than for the paragraph, which allows to establish the cause-and-effect: the sentence is a parent for the paragraph. So searching "Does Alice exercise merrily?" you may get the answer "Alice is tired".

      United States Patent 8,516,013

      14. The computer system of claim 9 in which said facility configured to extract predicative phrases is further configured to assign to the subtexts information regarding the date of their origin.

      AI database is a blockchain technology.

      1. I.Geller Bronze badge

        Microsoft and dictionary

        Microsoft Corp. today debuted a new version of its Power BI, which competes in the same category as Tableau Software Inc. Analysts can now extend the tool’s default vocabulary with technical terms unique to their industry, company-specific terms and synonyms to help it answer queries more accurately.

        I told you a few hours ago, didn't I?

        If the computer does not see individual words, their parts of speech and dictionary definitions - it can not construct the pattern "Alice trains a lot - 0.5" and the information is lost. Do you want to search your database knowing that you are destined to lose? Because of that Microsoft allowed to add technical terms and synonyms.

        A dictionary is a universal index, that is the same definition can be used at any time and in any place. Therefore, in AI database you can instantly find everything you want, nothing is lost and Microsoft drifts toward this database.

        What companies like OpenAI offer? They create their own dictionaries, which contain definitions only on phrases (patterns), not on singular words. Also, OpenAI uses not reduced to a single system and form, the same definitions but different texts. I guess Microsoft doesn't want OpenAI idea and decided to use words.

    2. RichardB

      Re: n-gram parsing vs. AI-parsing.

      All goes to pot once you realise that Merrily is the name of their horse.

      1. I.Geller Bronze badge

        Merrily as a name

        No. AI analyzes everything in context, taking into account subtexts - i.e., for example, dictionary definitions. If the AI sees that Merrily is a name, it will add it as a name. This is AI database.

        United States Patent 8,447,789

  3. John Brown (no body) Silver badge
    Paris Hilton

    for $15.7bn

    Is this going to be another HP/Autonomy?

    1. I.Geller Bronze badge

      Re: for $15.7bn


      1. Eek

        Re: for $15.7bn

        I wonder how much of the sales pitch will be "we can get those Tableau customers to also buy SalesForce"

    2. Gordon 10

      Re: for $15.7bn

      When a multi-billion dollar tech company buys another multi-billion dollar tech company the result is ALWAYS a car crash.

      1. Korev Silver badge

        Re: for $15.7bn

        Do they provide analytics to the car industry?

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