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These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:01,000 Presenter: Let's talk a little bit about 2 00:00:01,000 --> 00:00:03,000 the different types of storage 3 00:00:03,000 --> 00:00:05,000 and connection modes in Power BI. 4 00:00:05,000 --> 00:00:07,000 In this course, all of the data sources 5 00:00:07,000 --> 00:00:08,000 that we'll connect to 6 00:00:08,000 --> 00:00:11,000 will use import storage mode 7 00:00:11,000 --> 00:00:13,000 but it's really important to understand 8 00:00:13,000 --> 00:00:16,000 that Power BI actually supports several different types 9 00:00:16,000 --> 00:00:18,000 of storage and connection modes 10 00:00:18,000 --> 00:00:19,000 and that they're each useful 11 00:00:19,000 --> 00:00:21,000 in different types of scenarios. 12 00:00:22,000 --> 00:00:24,000 Import mode is the default storage mode 13 00:00:24,000 --> 00:00:27,000 where tables are stored in memory within Power BI 14 00:00:27,000 --> 00:00:30,000 and queries are fulfilled by cached data. 15 00:00:30,000 --> 00:00:32,000 Import data sets are really useful 16 00:00:32,000 --> 00:00:35,000 when you need fast query performance, 17 00:00:35,000 --> 00:00:36,000 and the dataset will be less 18 00:00:36,000 --> 00:00:38,000 than one gigabyte after compression. 19 00:00:38,000 --> 00:00:40,000 These are also super handy when 20 00:00:40,000 --> 00:00:42,000 the source data doesn't change frequently 21 00:00:42,000 --> 00:00:45,000 and when you don't need restrictions on Power Query, 22 00:00:45,000 --> 00:00:49,000 the data modeling, and then DAX functions. 23 00:00:49,000 --> 00:00:51,000 Direct query tables are connected directly 24 00:00:51,000 --> 00:00:53,000 to the source data and any queries, 25 00:00:53,000 --> 00:00:55,000 meaning data requests, that are needed 26 00:00:55,000 --> 00:00:57,000 are pushed back to the source 27 00:00:57,000 --> 00:00:59,000 to be executed on demand. 28 00:00:59,000 --> 00:01:02,000 This storage method is most commonly used 29 00:01:02,000 --> 00:01:03,000 when data sets are too large 30 00:01:03,000 --> 00:01:05,000 to be stored in memory 31 00:01:05,000 --> 00:01:08,000 and the source data updates very frequently, 32 00:01:08,000 --> 00:01:11,000 and reports must reflect the most recent data. 33 00:01:11,000 --> 00:01:14,000 Additionally, this is commonly used 34 00:01:14,000 --> 00:01:15,000 when a company policy states 35 00:01:15,000 --> 00:01:17,000 that data can't be imported 36 00:01:17,000 --> 00:01:19,000 but can only be accessed 37 00:01:19,000 --> 00:01:20,000 from the original source. 38 00:01:21,000 --> 00:01:23,000 Composite models, as you may 39 00:01:23,000 --> 00:01:25,000 have already guessed by the name, 40 00:01:25,000 --> 00:01:27,000 are models that contain a mixture 41 00:01:27,000 --> 00:01:29,000 of both import and direct query modes 42 00:01:29,000 --> 00:01:33,000 or are created from multiple direct query tables. 43 00:01:33,000 --> 00:01:36,000 Composite models are useful in cases where you 44 00:01:36,000 --> 00:01:39,000 want to really boost your data model performance 45 00:01:39,000 --> 00:01:41,000 by setting appropriate storage types 46 00:01:41,000 --> 00:01:44,000 for each table or combine a direct query model 47 00:01:44,000 --> 00:01:46,000 with additional imported data, 48 00:01:46,000 --> 00:01:47,000 or create a single model 49 00:01:47,000 --> 00:01:51,000 from two or more direct query models. 50 00:01:51,000 --> 00:01:53,000 And our last option here, 51 00:01:53,000 --> 00:01:54,000 live connections are used to connect 52 00:01:54,000 --> 00:01:57,000 to pre-published Power BI data sets 53 00:01:57,000 --> 00:01:59,000 from sources like Power BI Service 54 00:01:59,000 --> 00:02:01,000 and Azure Analysis services. 55 00:02:01,000 --> 00:02:02,000 Live connections are great 56 00:02:02,000 --> 00:02:05,000 because they create one data set that serves 57 00:02:05,000 --> 00:02:07,000 as a central source of truth. 58 00:02:07,000 --> 00:02:09,000 All team members can author 59 00:02:09,000 --> 00:02:10,000 and create multiple different reports 60 00:02:10,000 --> 00:02:13,000 from the same underlying source, 61 00:02:13,000 --> 00:02:16,000 and it also helps multi developer teams work 62 00:02:16,000 --> 00:02:18,000 more efficiently and seamlessly, 63 00:02:18,000 --> 00:02:20,000 where one team member may build the model 64 00:02:20,000 --> 00:02:23,000 and another team member works on the visualization. 65 00:02:24,000 --> 00:02:26,000 As I mentioned at the start of this lecture, 66 00:02:26,000 --> 00:02:29,000 we're gonna be importing all of our data sets 67 00:02:29,000 --> 00:02:31,000 into Power BI's memory, 68 00:02:31,000 --> 00:02:33,000 and we'll be using import mode. 69 00:02:33,000 --> 00:02:34,000 From a little bit of a higher level, 70 00:02:34,000 --> 00:02:36,000 part of your role as an analyst 71 00:02:36,000 --> 00:02:38,000 or a Power BI developer 72 00:02:38,000 --> 00:02:41,000 may be to recommend data connection strategies 73 00:02:41,000 --> 00:02:44,000 based on the business case or the business need. 74 00:02:44,000 --> 00:02:45,000 The point here is that 75 00:02:45,000 --> 00:02:48,000 I don't wanna cover all of the intricacies 76 00:02:48,000 --> 00:02:51,000 and nuances of each of these connection modes, 77 00:02:51,000 --> 00:02:53,000 but rather, I really just wanna help 78 00:02:53,000 --> 00:02:55,000 make you aware that there are different ways 79 00:02:55,000 --> 00:02:57,000 that you can connect to data within Power BI, 80 00:02:57,000 --> 00:02:59,000 and that the reasons 81 00:02:59,000 --> 00:03:01,000 for using those are going to vary. 82 00:03:01,000 --> 00:03:04,000 So each of these storage modes definitely 83 00:03:04,000 --> 00:03:06,000 has different types of features and restrictions, 84 00:03:06,000 --> 00:03:09,000 and limitations and upsides and considerations, 85 00:03:09,000 --> 00:03:12,000 and it's really important to read more 86 00:03:12,000 --> 00:03:14,000 about each type of these storage modes 87 00:03:14,000 --> 00:03:16,000 prior to using it. 88 00:03:16,000 --> 00:03:17,000 All right, so with that, 89 00:03:17,000 --> 00:03:19,000 we're gonna jump into our next lecture. 6635

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