01
Tur Lab Interaktif Google Cloud
Dalam lab interaktif yang pertama ini, Anda akan mengakses konsol Google Cloud, serta menggunakan beberapa fitur dasar Google Cloud: Project, Resource, Pengguna IAM, Peran, Izin, dan API.
Data Analyst Learning Path
Data Analyst mengumpulkan dan menganalisis data untuk mengidentifikasi tren dan mengembangkan informasi berharga untuk membantu memecahkan masalah. Jalur pembelajaran ini memandu Anda menjalani sejumlah kursus sesuai permintaan, lab, dan badge keterampilan pilihan yang memberi Anda pengalaman nyata dan langsung menggunakan teknologi Google Cloud yang penting untuk peran Data Analyst. Setelah Anda menyelesaikan jalur, lihat katalog kami yang menawarkan 700+ lab dan kursus untuk melanjutkan karier profesional Anda.
02
Introduction to Data Analytics on Google Cloud
This introductory course explores the basics of data analysis, including collection, storage, exploration, visualization, and sharing. This course also introduces Google Cloud's data analytics tools and services. Through video lectures, demos, quizzes, and hands-on labs, this course demonstrates how to...
03
Analyzing and Visualizing Data in Looker
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's...
04
Developing Data Models with LookML
This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start...
05
Prepare Data for ML APIs on Google Cloud
Selesaikan badge keahlian pengantar Prepare Data for ML APIs on Google Cloud untuk menunjukkan keterampilan Anda dalam hal berikut: menghapus data dengan Dataprep by Trifacta, menjalankan pipeline data di Dataflow, membuat cluster dan menjalankan tugas Apache Spark di Dataproc, dan...
06
Prepare Data for Looker Dashboards and Reports
Selesaikan badge keahlian pengantar Prepare Data for Looker Dashboards and Reports untuk menunjukkan keterampilan Anda dalam hal berikut: memfilter, mengurutkan, dan melakukan pivot data, menggabungkan hasil dari berbagai Jelajah di Looker, serta menggunakan fungsi dan operasi guna membuat dasbor dan...
07
Derive Insights from BigQuery Data
Selesaikan badge keahlian pengantar Derive Insights from BigQuery Data untuk menunjukkan keterampilan dalam hal berikut: menulis kueri SQL, membuat kueri tabel publik, memuat sampel data ke dalam BigQuery, memecahkan masalah error sintaksis umum dengan validator kueri di BigQuery, dan membuat...
08
Create ML Models with BigQuery ML
Selesaikan badge keahlian tingkat menengah Create ML Models with BigQuery ML untuk menunjukkan keterampilan dalam hal berikut ini: membuat dan mengevaluasi model machine learning dengan BigQuery ML untuk membuat prediksi data. Badge keahlian merupakan badge digital eksklusif yang diberikan oleh...
09
Applying Advanced LookML Concepts in Looker
In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and...
10
Data Catalog Fundamentals
Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets...
11
Build LookML Objects in Looker
Complete the introductory Build LookML Objects in Looker skill badge to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining...
12
Manage Data Models in Looker
Complete the intermediate Manage Data Models in Looker skill badge to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived...