1 00:00:00,550 --> 00:00:03,660 Hello, and welcome to a brand new section. 2 00:00:03,660 --> 00:00:04,610 In this section, 3 00:00:04,610 --> 00:00:08,470 we are going to be talking about batch processing solutions. 4 00:00:08,470 --> 00:00:10,560 So let's get started. 5 00:00:10,560 --> 00:00:12,600 So as we look at this section, 6 00:00:12,600 --> 00:00:14,770 there's a few things that I want to highlight. 7 00:00:14,770 --> 00:00:19,010 The first, we will be discussing the foundations of batch. 8 00:00:19,010 --> 00:00:21,140 So we're going to be talking about concepts 9 00:00:21,140 --> 00:00:24,390 and then how to tie those concepts to services. 10 00:00:24,390 --> 00:00:26,300 So keep that kind of in the back of your head 11 00:00:26,300 --> 00:00:29,140 as we look through different lessons. 12 00:00:29,140 --> 00:00:29,973 Second, we're going to be doing a deep dive 13 00:00:29,973 --> 00:00:30,806 into Data Factory. 14 00:00:33,050 --> 00:00:34,820 Keep in mind, we talked about Data Factory 15 00:00:34,820 --> 00:00:36,550 being that orchestration service 16 00:00:36,550 --> 00:00:38,930 that moves data and other things. 17 00:00:38,930 --> 00:00:41,450 But as we talk about Data Factory, 18 00:00:41,450 --> 00:00:43,460 keep in mind that these concepts, 19 00:00:43,460 --> 00:00:45,780 especially around pipelines, can transfer 20 00:00:45,780 --> 00:00:48,870 into other areas such as Azure Synapse Analytics, 21 00:00:48,870 --> 00:00:49,813 for an example. 22 00:00:50,880 --> 00:00:54,590 Third, this is a design and implement section. 23 00:00:54,590 --> 00:00:56,450 So think about that as we learn. 24 00:00:56,450 --> 00:00:58,410 So as we talk about batch concepts, 25 00:00:58,410 --> 00:01:00,630 I want you to be thinking about those concepts 26 00:01:00,630 --> 00:01:03,510 and how you could tie that into real-world scenarios 27 00:01:03,510 --> 00:01:05,110 that might be going on at your work. 28 00:01:05,110 --> 00:01:06,080 And not only that, 29 00:01:06,080 --> 00:01:09,650 but also tying it into what Azure services you would use. 30 00:01:09,650 --> 00:01:11,510 As you start to think through that way, 31 00:01:11,510 --> 00:01:13,890 it's going to help you become a better data engineer, 32 00:01:13,890 --> 00:01:16,343 and it's going to help you pass that DP-203. 33 00:01:18,210 --> 00:01:20,740 Finally, a few key points to remember. 34 00:01:20,740 --> 00:01:22,970 First, stay hungry. 35 00:01:22,970 --> 00:01:24,540 What's your next reward? 36 00:01:24,540 --> 00:01:28,770 So we are probably a third to a halfway through this course. 37 00:01:28,770 --> 00:01:30,780 Make sure that you have a few little rewards 38 00:01:30,780 --> 00:01:32,360 for yourself along the way. 39 00:01:32,360 --> 00:01:33,537 That may be as simple as, 40 00:01:33,537 --> 00:01:35,067 "Hey, when I finish section 5, 41 00:01:35,067 --> 00:01:36,570 "I'm going to go get my favorite snack" 42 00:01:36,570 --> 00:01:38,627 or "I'm going to give myself a night off 43 00:01:38,627 --> 00:01:41,470 "and I'm going to go do something fun that I enjoy doing." 44 00:01:41,470 --> 00:01:44,650 Make sure that you plan those into your study 45 00:01:44,650 --> 00:01:46,818 because that's going to help you be more successful 46 00:01:46,818 --> 00:01:49,930 and help you push through the doldrums, right? 47 00:01:49,930 --> 00:01:51,420 So when you get about halfway through our course, 48 00:01:51,420 --> 00:01:52,470 a little bit further, 49 00:01:52,470 --> 00:01:55,284 you start getting into the, man, I'm getting really tired. 50 00:01:55,284 --> 00:01:56,960 These little rewards can help 51 00:01:56,960 --> 00:01:58,570 you push through that. 52 00:01:58,570 --> 00:02:02,590 Two, repetition, and this carries for the entire course. 53 00:02:02,590 --> 00:02:04,280 Keep in mind as we go, 54 00:02:04,280 --> 00:02:06,670 key services, key concepts. 55 00:02:06,670 --> 00:02:08,970 Those things have to marry together, 56 00:02:08,970 --> 00:02:11,510 and the repetition can help you both in the lessons 57 00:02:11,510 --> 00:02:12,450 to tie it together, 58 00:02:12,450 --> 00:02:15,450 but specifically as we talk about labs, 59 00:02:15,450 --> 00:02:18,630 repetition in those labs is going to help you 60 00:02:18,630 --> 00:02:22,760 to take those services and concepts and tie them together. 61 00:02:22,760 --> 00:02:25,000 Finally, don't forget about the code. 62 00:02:25,000 --> 00:02:27,190 So some of the lessons we talk about code. 63 00:02:27,190 --> 00:02:29,420 Some of the lessons we don't talk about code, 64 00:02:29,420 --> 00:02:33,010 but you do need to understand the basic concepts of code. 65 00:02:33,010 --> 00:02:34,930 You don't need to memorize the code, 66 00:02:34,930 --> 00:02:37,387 but you do need to be able to glance through and say, 67 00:02:37,387 --> 00:02:39,777 "Okay, I know roughly what you're trying to tell me 68 00:02:39,777 --> 00:02:41,440 "and I could see where there might be an error," 69 00:02:41,440 --> 00:02:44,290 or as we talk about concepts, I can look at some code 70 00:02:44,290 --> 00:02:45,297 and say, "Hmm, I don't think 71 00:02:45,297 --> 00:02:47,410 "you're using the right service." 72 00:02:47,410 --> 00:02:50,430 That's going to help you as you move through the course. 73 00:02:50,430 --> 00:02:52,360 All right. Short and sweet. 74 00:02:52,360 --> 00:02:53,380 Without further ado, 75 00:02:53,380 --> 00:02:55,920 let's end this lesson and dive a little further 76 00:02:55,920 --> 00:02:59,180 into our section on batch processing. 77 00:02:59,180 --> 00:03:00,387 See you there.