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August 2008 - Posts

  • Re-using Filters in Widgets and Custom Measures

    If you’ve dug around the product and/or the online documentation, you must have encountered the filtering and segmentation features Prism offers.   If not, this is a good time to get acquainted with this powerful feature here.


    The first advantage of a Prism filter is that it allows you to filter your dimensions to focus only on the members that interest you, such as your best customers in terms of sales, products with a positive selling growth, the 20% of customers that account for 80% of your revenue, etc.


    These filters are saved in your repository (under the corresponding dimension’s Filters node in the data browser) and always return the members that fit the filter’s definition at any specific point in time.  Requesting results for the “Best Customers in terms of Sales” today, may not yield the same results tomorrow because the best customers changed during the night.


     

     

    So, what can you do with these filters once you create them?  This short article will show you how you can use the same filter to achieve multiple business goals, without having to put in any extra work.
     

     

    1. Calculate Filter Member Values or - "Show me the total sales for each one of my best customers"

    Placing the filter on the Rows (or Columns) panel with one or measures, will calculate the values of the measure(s) for each of the members returned by the filter. The filter returns Customers B, C, H, L and T which are the best 5 customers in terms of sales.  The following pivot calculates the Sales measure for each of these customers.

     

     

     

    2. Calculate values in the context of a filter or - "Show me how much sales my best customers produced in each of my store cities"

    Placing the filter on the background panel will present the pivot values for the filter members only.  The following pivot will show the total sales just for customers belonging to the filter for each store city.  Note that since the filter is placed on the background, it is calculated for all stores, not for a specific store.


     

     

    3. Calculate filter for members individually or - "Show me the best customers for each one of my store cities, and their sales"

    The same 'Best 5 Customers' filter we created can be used to calculate the best 5 customers for each city individually.  If you place this filter immediately after the Store City dimension, Prism will behave like this automatically.  The following pivot shows the best 5 customers in terms of sales for each store city individually.  You will notice that this filter returns different customers for each city.

     

     

     

    4. Using a Filter to Scope a Measure or - "Show me the total sales of each store city's best customers, without showing me the list of customers"

    My Excel file has a 'Sales' measure.  I would like to create a new Measure that is called 'Sales for Best Customers' that I can use again and again in my reports.  If you have yet to explore Prism's custom measures capabilities, now would be a good time to learn.

     

    Prism introduces a concept called 'Measured Values'.  In simple terms, they are expressions that include a measure (or custom measure) and a scope in which to calculate.  Measured Values contain a single measure and (at most) a single representative from each available dimension.  They are defined by enclosing the list of measures and representatives in parentheses while separating each Measured Value element with commas.

     
    The following formula is created by dropping the 'Sales' measure and 'Best 5 Customers (Sales)' filter onto the formula editor, and adding parentheses and a comma.  This tells Prism to calculate the Sales measure in the context of the Best 5 Customers filter. We'll call this custom measure 'Sales Of Best Customers'.

     

    Placing this new formula on a pivot with the Store City dimension will yield the total sales of best customers for each store individually.  This is because the filter within the formula still works within the context of the current members on the pivot.  If you add subtotals to the pivot in section 3 you will notice that the values of this new pivot match the values of the subtotals.
     

     

     

     

    5. Aggregating a Filter or - "Show me the average sales for each store city's best customers"

    Filters can also be aggregated over a measure using one of the defined aggregation functions - Sum, Avg, Min, Max, Count, DupCount.  What aggregation functions do is calculate the value of a measure for each member in the filter and then aggregates all the values according to the specified function.

    The following formula calculates the average sales to 'Best 5 Customers (Sales)':

     

    Placing this formula on a pivot with the Store City dimension will yield the average sales to the best 5 customers in each city.

     

  • SiSense Prism for Google Spreadsheets or: Now you can create a dashboard with Google Spreadsheets

    For some time now, we've been looking at including Google spreadsheets as one of the data sources that SiSense Prism supports.  We've just launched this, in a public beta, and I wanted to tell you why I think this is an important move.

    Our philosophy is to support as many data sources as possible. We want to enable the user to do IT-less business intelligence: analytics, charting and dashboarding, on any data source. In the future we'll mash up the different data sources, catapulting everyone into business intelligence heaven….


    Google spreadsheets is a unique & interesting data source: an online, sharable spreadsheet.
    These features promise real operational value. Let's talk about a use case. 

    Well… as Jonathan Rochelle and Nir Bar Lev blogged on the official Google blog, there are many uses for Google spreadsheets:

    "Sure, there are definitely favorite themes -- sports, finance and, yes, knitting -- but then the examples become so particular to the people and groups who are using them: The beer taster's results. The nursery school class schedule. The biker's riding log. The family reunion plan. The ski-trip sign-up form. Endless examples, all of which, to spreadsheet junkies like us, are interesting".

    Let us try an example: A small business decides to use Google spreadsheets to unify data from its small business CRM and financial systems. It doesn't want anything fancy: just the top grossing products as sold by the top ranked salespeople. Or perhaps, top financially contributing customers. Google spreadsheets is a classic for them: they can unify the data and share it in real time, and this requires no IT. But…. Google spreadsheets has little in terms of charting and even less in terms of analytics. No pivot tables… no KPIs (key performance indicators, in our case "contribution per customer"). No filters (top sales people as measured by some value).  How can they do this? They were planning on distributing the resulting dashboard to the salespeople, so they see how they measure up.

     

    SiSense Prism, as you've probably guessed, does all this and more. It really delivers on providing analytics and charting in a way that really requires no IT and no programming or scripting. You just need common sense. In our use case, each of the traveling salespeople can then check the KPIs or dashboard created with Prism, using the Google spreadsheets data. He could immediately tell whether he needs to pound the pavement and look for more sales, or whether he can afford a leisurely night at the hotel bar…

     

    "OK, OK" you'll tell me, a bit annoyed, "aren't there pivot tables and charting for Google spreadsheets?"

    Well, let me explain why I think our new release of SiSense for Google Spreadsheets is more exciting than that.

     

    Pivots in Google spreadsheets are limited to the data inside: so a formula like contribution per customer cannot be done on the business intelligence level. These are called multi-dimensional formulas. Filters (top 10 salespeople) are difficult to implement. With SiSense you can do all that. For instance, using our "filter" feature you can get at a much deeper analytics result, with no coding, scripting or IT effort. Check out our filtering feature here. You can easily create a "top ten earning salesmen" or a "ten best opening lines to sell" as well as a "people who bought this also bought this" table, "top grossing products" etc. Doing this with Google spreadsheets today is fairly difficult and would require scripting, programming etc, as well as purchasing and installing the middle tier for the data warehouse. At best, in a cloud model, you'd need to pull in someone that can create a data warehouse for business intelligence.

     

    We can do this for any user. The reason is that we use Google spreadsheets as a data source, and query it directly in our in-memory database. We also don't require that the user "know" how to build an OLAP, or scripting for BI. From his point of view, we do all of this on the fly, seamlessly and transparently. Anytime you synchronize with Google spreadsheets, the most recent data will be reflected in the dashboard (dashboards are authored with a WYSIWYG interface).

    Any other approach (even in the cloud) will require a programmer to build MDX queries, create a server etc.

    In the long run, users won't let themselves be limited by the 10,000 row limit on google spreadsheets. They can "offload" data from last month, and store it offline. With SiSense they can then join the past and present data, getting a current and historical perspective on performance, without losing anything.

    Tell us what you think about SiSense for Google Spreadsheets, or send us your favorite examples, and we'll feature them on the blog.