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Posts by Ziv Himmelfarb

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What is a Data Warehouse?

Ziv Himmelfarb
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What is a Data Warehouse ? From a purely technical, low-level, standpoint, a Data Warehouse is a database like any other. It has tables with relations between them, indexes, views, sequences etc. Data Warehouses are typically large. They are used for storing all the data the organization needs in order to make data-driven decisions. It’s a “warehouse” because you collect all of your relevant data, from all of your databases(and sometimes external sources) and store it in the warehouse. Modern data warehouses are built as a collection of data marts developed one after the other in short, agile sprints. All data from all sources is collected into one place which ideally operates using one technology. A company can have several…

5 Power BI Tips (2nd edition)

Ziv Himmelfarb
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A few months ago I wrote a few tips for Power BI users. Here are 5 more! Use the “Edit interactions” option Your visuals interact with each other. If you have a table and a pie chart on your page, clicking on a piece of the pie acts as a filter on the table. This is the default behaviour, but you can control which visuals interact with each other, and disable filtering if you want to.This is very useful when you want to display a mixture of static and dynamic data on the same page. For instance, you want a chart to show performance based on a date slicer, but you also want to display a few “Last 30 Days”…

Calculated Columns and Measures in Power BI

Ziv Himmelfarb
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With Power BI, as is the case with other BI products, you can load your data and start analysing it. The data can come from almost any possible source: relational databases, excel spreadsheet, online services, text files and what not. Furthermore, the data can come from more than one source, allowing you to use Power BI as an integration tool. I’m pretty vocal against using Power BI, or any other BI platform to integrate data from different sources. I’ve talked about it a little bit here. The gist is that it’s better to integrate your sources into a data warehouse or data marts,and connect Power BI to them. That way they are independent of trends in the BI space, and can serve as…

The Date Dimension in modern BI systems

Ziv Himmelfarb
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One of the most common dimension tables in any data warehouse or data mart is the date dimension. It typically stores, for each date relevant to the organisation, a few fields which describe that date, such as: year, month, month name, work day(yes/no), financial year, quarter, day name, and the list goes on, depending on what you need. When connecting the date dimension with your fact tables, it makes it easy to answer questions like “what’s the most profitable day of the week”, “what are the business results of the 3rd quarter” etc. Here’s a glimpse:   Modern BI visualisation products (namely where I’ve seen this: Tableau and Power BI) often have a built-in functionality that serves as a date dimension.…

Power BI Desktop July 2017 Update

Ziv Himmelfarb
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The July 2017 Power BI Desktop update is a good one. There are two highlights as far as I’m concerned .The first one is the ability to customise field names in visuals, and override the names defined in the dataset. It’s very useful, and in fact I’ve talked about it almost a year ago in my Power BI Wishlist article. The second highlight is relative date filters. We’ve already had relative date slicers, now we have filters as well. This is very important in case you prefer not to waste screen space on slicers, and still want to use the relative filters. Other new features include new quick measures (including a super-cool star rating calculation), GA of the new table…

Power BI Apps: The good, the bad, and the ugly

Ziv Himmelfarb
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Power BI apps, announced and released just a few weeks ago, is a very big change to how content is published and shared over Power BI. I had some initial thoughts, but wanted to use it for a few weeks before I share them. 3 weeks later, here’s the deal. From the user perspective: Apps are great In a nutshell, apps replace content packs. Apps are basically a shiny (if it was 2008) way to describe folders of content. Let’s say you have sales reports, marketing reports, and finance reports. Until apps where introduced, a very common way to share was to create content packs per topic, so we would have had a sales content pack, a marketing content pack,…

5 Power BI Tips

Ziv Himmelfarb
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A few helpful tips I wish I’ve read before I started with Power BI. Refresh before you publish, if you can. For existing reports which you are changing, before you click on the publish button, remember that publishing a report means overriding the underlying dataset. So, first refresh the dataset in Power BI desktop, and then publish. If you don’t do that, your users will see old data. When the publish operation is done, the service immediacy starts a data refresh, but if it’s a big dataset, it could take a while. So just remember to refresh before you publish. But…be careful if it’s a large dataset An exception to the previous, if your Power BI desktop file nears the…

Usage Stats as a building block, not an afterthought

Ziv Himmelfarb
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At the beginning of 2012, I was asked to come up with a way for the product management team to be able to understand how areas of the product are being used. We’ve already had the usual marketing, sales and conversion data, and some statistics about retention, but the idea was to stop guessing why a specific feature produced a specific result, and actually know why. Together with our platform developers, we’ve started a “usage stats” project which basically meant writing logs about everything the users do(using our system of course…), and producing reports on them. “Everything” means what screens they browse, which forms they start filling, how much time they spend doing what they do and what messages do…
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