Menu

Zaloguj się

Twoje konto

×
Dodano do koszyka:
Pozycja znajduje się w koszyku, zwiększono ilość tej pozycji:
Zakupiłeś już tę pozycję:
Książkę możesz pobrać z biblioteki w panelu użytkownika
Pozycja znajduje się w koszyku
Przejdź do koszyka

Zawartość koszyka

ODBIERZ TWÓJ BONUS :: »

Szukaj

Zamknij

    Dostawa od 0,00zł

    TOP tytuł w super cenie » 50% taniej

    Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL Raghav Kandarpa, Shivangi Saxena

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL Raghav Kandarpa, Shivangi Saxena - okladka książki

    Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL Raghav Kandarpa, Shivangi Saxena - okladka książki

    Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL Raghav Kandarpa, Shivangi Saxena - audiobook MP3

    Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL Raghav Kandarpa, Shivangi Saxena - audiobook CD

    Autorzy:
    Raghav Kandarpa, Shivangi Saxena
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    350
    Dostępne formaty:
         PDF
         ePub
    The amount of data generated continues to grow rapidly, making it increasingly important for businesses to be able to wrangle this data and understand it quickly and efficiently. Although data wrangling can be challenging, with the right tools and techniques you can efficiently handle enormous amounts of unstructured data.
    The book starts by introducing you to the basics of SQL, focusing on the core principles and techniques of data wrangling. You’ll then explore advanced SQL concepts like aggregate functions, window functions, CTEs, and subqueries that are very popular in the business world. The next set of chapters will walk you through different functions within SQL query that cause delays in data transformation and help you figure out the difference between a good query and bad one. You’ll also learn how data wrangling and data science go hand in hand. The book is filled with datasets and practical examples to help you understand the concepts thoroughly, along with best practices to guide you at every stage of data wrangling.
    By the end of this book, you’ll be equipped with essential techniques and best practices for data wrangling, and will predominantly learn how to use clean and standardized data models to make informed decisions, helping businesses avoid costly mistakes.

    Wybrane bestsellery

    Selling helion.pl

    O autorach książki

    Raghav Kandarpa is an experienced Data Scientist in Finance and logistics industry with expertise in SQL, Python, Building Machine Learning Models, Financial Data Modelling, and Statistical Analysis. He holds a Masters’ degree in Business Analytics specializing in Data Science from the University of Texas at Dallas.
    Shivangi Saxena is an experienced BI Engineer with proficiency in SQL, Data Visualization, and Statistical Analysis. She holds a master’s degree in Information Technology and Management from the University of Texas at Dallas. She has several years of experience building several BI tools and products using SQL and BI reporting tools which has helped stakeholders to get visibility to the right data points

    Packt Publishing - inne książki

    Zamknij

    Przenieś na półkę

    Proszę czekać...
    ajax-loader

    Zamknij

    Wybierz metodę płatności

    Ebook
    116,10 zł
    Dodaj do koszyka

    Wydawnictwo Naukowe Helion »

    Grafika Wydawnictwo Naukowe Helion. Dołącz do nas!
    Zamknij Pobierz aplikację mobilną Ebookpoint
    Zabrania się wykorzystania treści strony do celów eksploracji tekstu i danych (TDM), w tym eksploracji w celu szkolenia technologii AI i innych systemów uczenia maszynowego. It is forbidden to use the content of the site for text and data mining (TDM), including mining for training AI technologies and other machine learning systems.