Azure Data Factory Cookbook 2nd Edition by Dmitry Foshin 1803241821 9781803241821

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Product details:

ISBN-10 :  1803241821 

ISBN-13 :  9781803241821

Author:  Dmitry Foshin 

This new edition of the Azure Data Factory book, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF. There are updated and new recipes throughout the book based on developments happening in Azure Synapse, Deployment with Azure DevOps, and Azure Purview. The current edition also runs you through Fabric Data Factory, Data Explorer, and some industry-grade best practices with specific chapters on each. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. You’ll familiarize yourself with the common errors that you may encounter while working with ADF and find out the solutions to them. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF with its latest advancements as the main ETL and orchestration tool for your data warehouse projects.

Azure Data Factory Cookbook 2nd table of contents:

1. Who this book is for
2. What this book covers
3. To get the most out of this book
4. Get in touch
5. Getting Started with ADF
6. Introduction to the Azure data platform
7. Getting ready
8. How to do it…
9. How it works…
10. Creating and executing our first job in ADF
11. Getting ready
12. How to do it…
13. How it works…
14. There’s more…
15. See also
16. Creating an ADF pipeline using the Copy Data tool
17. Getting ready
18. How to do it…
19. How it works…
20. There’s more…
21. Creating an ADF pipeline using Python
22. Getting ready
23. How to do it…
24. How it works…
25. There’s more…
26. See also
27. Creating a data factory using PowerShell
28. Getting ready
29. How to do it…
30. How it works…
31. There’s more…
32. See also
33. Using templates to create ADF pipelines
34. Getting ready
35. How to do it…
36. How it works…
37. See also
38. Creating an Azure Data Factory using Azure Bicep
39. Getting ready
40. How to do it…
41. How it works…
42. There’s more…
43. See also
44. Orchestration and Control Flow
45. Technical requirements
46. Using parameters and built-in functions
47. Getting ready
48. How to do it…
49. How it works…
50. There’s more…
51. See also
52. Using the Metadata and Stored Procedure activities
53. Getting ready
54. How to do it…
55. How it works…
56. There’s more…
57. Using the ForEach and Filter activities
58. Getting ready
59. How to do it…
60. How it works…
61. Chaining and branching activities within a pipeline
62. Getting ready
63. How to do it…
64. There’s more…
65. Using the Lookup, Web, and Execute Pipeline activities
66. Getting ready
67. How to do it…
68. How it works…
69. There’s more…
70. See also
71. Creating event-based pipeline triggers
72. Getting ready
73. How to do it…
74. How it works…
75. There’s more…
76. See also
77. Setting Up Synapse Analytics
78. Technical requirements
79. Creating an Azure Synapse workspace
80. Getting ready
81. How to do it…
82. There’s more…
83. Loading data to Azure Synapse Analytics using Azure Data Factory
84. Getting ready
85. How to do it…
86. How it works…
87. There’s more…
88. Loading data to Azure Synapse Analytics using Azure Data Studio
89. Getting ready
90. How to do it…
91. How it works…
92. There’s more…
93. Loading data to Azure Synapse Analytics using bulk load
94. Getting ready
95. How to do it…
96. How it works…
97. Pausing/resuming an Azure Synapse SQL pool from Azure Data Factory
98. Getting ready
99. How to do it…
100. How it works…
101. There’s more…
102. Working with Azure Purview using Azure Synapse
103. Getting ready
104. How to do it…
105. How it works…
106. There’s more…
107. Copying data in Azure Synapse Integrate
108. Getting ready
109. How to do it…
110. How it works…
111. Using a Synapse serverless SQL pool
112. Getting ready
113. How to do it…
114. How it works…
115. There’s more…
116. Working with Data Lake and Spark Pools
117. Technical requirements
118. Setting up Azure Data Lake Storage Gen2
119. Getting ready
120. How to do it…
121. There’s more…
122. Creating a Synapse Analytics Spark pool
123. Getting ready
124. How to do it…
125. How it works…
126. There’s more…
127. Integrating Azure Data Lake and running Spark pool jobs
128. Getting ready
129. How to do it…
130. How it works…
131. Building and orchestrating a data pipeline for Data Lake and Spark
132. Getting ready
133. How to do it…
134. How it works…
135. There’s more…
136. Working with Big Data and Databricks
137. Introduction
138. Technical requirements
139. Setting up an HDInsight cluster
140. Getting ready
141. How to do it…
142. How it works…
143. There is more…
144. Processing data from Azure Data Lake with HDInsight and Hive
145. Getting ready
146. How to do it…
147. How it works…
148. Building data models in Delta Lake and data pipeline jobs with Databricks
149. Getting ready
150. How to do it…
151. How it works…
152. There is more…
153. Ingesting data into Delta Lake using Mapping Data Flows
154. Getting ready
155. How to do it…
156. How it works…
157. There is more…
158. External integrations with other compute engines (Snowflake)
159. Getting ready
160. How to do it…
161. How it works…
162. There is more…
163. Data Migration – Azure Data Factory and Other Cloud Services
164. Technical requirements
165. Copying data from Amazon S3 to Azure Blob storage
166. Getting ready
167. How to do it…
168. How it works…
169. Copying large datasets from S3 to ADLS
170. Getting ready
171. How to do it…
172. Creating the linked services and dataset for the pipeline
173. Creating the inner pipeline
174. Creating the outer pipeline
175. How it works…
176. See also
177. Copying data from Google Cloud Storage to Azure Data Lake
178. Getting ready
179. How to do it…
180. How it works…
181. See also
182. Copying data from Google BigQuery to Azure Data Lake Store
183. Getting ready
184. How to do it…
185. Migrating data from Google BigQuery to Azure Synapse
186. Getting ready
187. How to do it…
188. See also
189. Extending Azure Data Factory with Logic Apps and Azure Functions
190. Technical requirements
191. Triggering your data processing with Logic Apps
192. Getting ready
193. How to do it…
194. How it works…
195. There’s more…
196. Using the Web activity to call an Azure logic app
197. Getting ready
198. How to do it…
199. How it works…
200. There’s more…
201. Adding flexibility to your pipelines with Azure Functions
202. Getting ready…
203. How to do it…
204. How it works…
205. There’s more…
206. Microsoft Fabric and Power BI, Azure ML, and Cognitive Services
207. Technical requirements
208. Introducing Microsoft Fabric and Data Factory
209. Getting ready
210. How to do it…
211. How it works…
212. Microsoft Fabric Data Factory: A closer look at the pipelines
213. Getting ready
214. How to do it…
215. How it works…
216. Loading data with Microsoft Fabric Dataflows
217. Getting ready
218. How to do it…
219. How it works…
220. There’s more…
221. Automatically building ML models with speed and scale
222. Getting ready
223. How to do it…
224. How it works…
225. There’s more…
226. Analyzing and transforming data with Azure AI and prebuilt ML models
227. Getting ready
228. How to do it…
229. How it works…
230. There’s more…
231. Managing Deployment Processes with Azure DevOps
232. Technical requirements
233. Setting up Azure DevOps
234. Getting ready
235. How to do it…
236. How it works…
237. Publishing changes to ADF
238. Getting ready
239. How to do it…
240. How it works…
241. Deploying your features into the master branch
242. Getting ready
243. How to do it…
244. How it works…
245. Getting ready for the CI/CD of ADF
246. Getting ready
247. How to do it…
248. How it works…
249. Creating an Azure pipeline for CD
250. Getting ready
251. How to do it…
252. How it works…
253. There’s more…
254. Install and configure Visual Studio to work with ADF deployment
255. Getting ready
256. How to do it…
257. How it works…
258. Setting up ADF as a Visual Studio project
259. Getting ready
260. How to do it…
261. How it works…
262. Running Airflow DAGs with ADF
263. Getting ready
264. How to do it…
265. How it works…
266. Monitoring and Troubleshooting Data Pipelines
267. Technical requirements
268. Monitoring pipeline runs and integration runtimes
269. Getting ready
270. How to do it…
271. How it works…
272. Investigating failures – running pipelines in debug mode
273. Getting ready
274. How to do it…
275. How it works…
276. There’s more…
277. See also
278. Rerunning activities
279. Getting ready
280. How to do it…
281. How it works…
282. Configuring alerts for your Azure Data Factory runs
283. Getting ready
284. How to do it…
285. How it works…
286. There’s more…
287. See also
288. Working with Azure Data Explorer
289. Introduction to ADX
290. See also
291. Creating an ADX cluster and ingesting data
292. Getting ready
293. How to do it…
294. How it works…
295. How it works…
296. See also
297. Orchestrating ADX data with Azure Data Factory
298. Getting ready
299. How to do it…
300. How it works…
301. There’s more…
302. See also
303. Ingesting data from Azure Blob storage to ADX in Azure Data Factory using the Copy activity
304. Getting ready
305. How to do it…
306. How it works…
307. There’s more…
308. The Best Practices of Working with ADF
309. Technical requirements
310. Setting up roles and permissions with access levels in ADF
311. Getting ready
312. How to do it…
313. How it works…
314. There is more…
315. See also
316. Setting up Meta ETL with ADF
317. Getting ready
318. How to do it…
319. How it works…
320. There’s more…
321. Leveraging ADF scalability: Performance tuning of an ADF pipeline
322. Getting ready
323. How to do it…
324. How it works…
325. There is more…
326. See also
327. Using ADF disaster recovery built-in features
328. Getting ready
329. How to do it…
330. How it works…
331. Change Data Capture
332. Getting ready
333. How to do it…
334. How it works…
335. There is more…
336. Managing Data Factory costs with FinOps
337. Getting ready
338. How to do it…
339. How it works…
340. Other Books You May Enjoy

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