Book Image

Hands-On Data Science with SQL Server 2017

By : Marek Chmel, Vladimír Mužný
Book Image

Hands-On Data Science with SQL Server 2017

By: Marek Chmel, Vladimír Mužný

Overview of this book

SQL Server is a relational database management system that enables you to cover end-to-end data science processes using various inbuilt services and features. Hands-On Data Science with SQL Server 2017 starts with an overview of data science with SQL to understand the core tasks in data science. You will learn intermediate-to-advanced level concepts to perform analytical tasks on data using SQL Server. The book has a unique approach, covering best practices, tasks, and challenges to test your abilities at the end of each chapter. You will explore the ins and outs of performing various key tasks such as data collection, cleaning, manipulation, aggregations, and filtering techniques. As you make your way through the chapters, you will turn raw data into actionable insights by wrangling and extracting data from databases using T-SQL. You will get to grips with preparing and presenting data in a meaningful way, using Power BI to reveal hidden patterns. In the concluding chapters, you will work with SQL Server integration services to transform data into a useful format and delve into advanced examples covering machine learning concepts such as predictive analytics using real-world examples. By the end of this book, you will be in a position to handle the growing amounts of data and perform everyday activities that a data science professional performs.
Table of Contents (14 chapters)

Importing flat files

Many information systems can provide us with flat files as a sort of exported data. We can import those flat files directly into SQL Server via Management Studio, where you can select the Import Flat File option from the database tasks. Then, you can choose to import the .csv or .txt files, which will be imported into a new table. While you're choosing the table name, you can also select, via the drop-down list, a schema for the table.

Flat files are also generated by many systems as log files, which can then be further analyzed in SQL Server as one of the possible tools. In such cases, the import would be more complex, since you would not aim for one file, but more for a folder structure containing hundreds or thousands of files, where the required data is stored.

Importing the content of a single flat file can be achieved via SQL Server Management...