Now that you have performed some data transformation exercises, it is a good time to read about some applicable transformation and data management concepts. Transformation As you progressed through the exercises that transformed the...
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Machine Learning– Transform, Manage, and Prepare Data
There are many techniques to consider when you want to better format data values for machine learning—or learning in general. Having data optimally organized increases the machine learning algorithm’s ability to efficiently predict and...
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Encode and Decode Data– Transform, Manage, and Prepare Data
There is a lot of history surrounding the encoding and decoding of data. Fundamentally, this concept revolves around how to store and render letter characters. As you know, all things that are computed must...
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Transform Data Using Stream Analytics – Transform, Manage, and Prepare Data
Remember, as you begin this section, that Chapter 7, “Design and Implement a Data Stream Processing Solution,” is devoted to data streaming. The content in this section will therefore target the Azure Stream Analytics...
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Azure HDInsight – Transform, Manage, and Prepare Data
If you provision an Azure HDInsight Apache Spark cluster, there exists a Jupyter notebook interactive environment. The Jupyter notebook environment is accessible by URL. If your HDInsight cluster is named brainjammer, for example, the...
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Jupyter Notebooks – Transform, Manage, and Prepare Data
Throughout the exercises in this book, you have created numerous notebooks. The notebooks are web‐based and consist of a series of ordered cells that can contain code. The code within these cells is what...
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Transform Data Using Transact‐SQL – Transform, Manage, and Prepare Data
Transact‐SQL (T‐SQL), as mentioned previously, is an extension of the SQL language developed by Microsoft. In this chapter and preceding chapters, you have read about and used T‐SQL statements, functions, and commands. Any time...
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Cleanse Data – Transform, Manage, and Prepare Data
%%pysparkdf = spark.read \.load(‘abfss://*@*.dfs.core.windows.net/SessionCSV/BRAINWAVES_WITH_ NULLS.csv’,format=’csv’, header=True) The final action to take after cleansing the data is to perhaps save it to a temporary table, using the saveAsTable(tableName) method, or into the Parquet file format....
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Shred JSON– Transform, Manage, and Prepare Data
When you shred something, the object being shredded is torn into small pieces. In many respects, it means that the pieces that result from being torn are in the smallest possible size. In this...
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Transform Data Using Apache Spark—Azure Synapse Analytics – Transform, Manage, and Prepare Data-1
Transform Data Using Apache SparkApache Spark can be used in a few products running on Azure: Azure Synapse Analytics Spark pools, Azure Databrick Spark clusters, Azure HDInsight Spark clusters, and Azure Data Factory. The...
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