Mempersiapkan Data untuk Eksplorasi

Go to Course: https://www.coursera.org/learn/mempersiapkan-data-untuk-eksplorasi

Introduction

### Course Review: Mempersiapkan Data untuk Eksplorasi **Overview** The "Mempersiapkan Data untuk Eksplorasi" (Preparing Data for Exploration) course is an integral part of the Google Data Analytics Certificate program offered on Coursera. This course is designed to equip beginners with the essential skills needed to pursue a career as a data analyst. Building on the foundations established in the previous two modules of the program, the course introduces valuable topics that enhance practical data analytics skills. By the end of the course, learners will have hands-on experience with key tools such as spreadsheets and will be prepared for real-world data analysis scenarios. **Syllabus Breakdown** The course syllabus is organized into five comprehensive sections: 1. **Tipe dan Struktur Data (Types and Structure of Data)** Here, learners dive into the vast world of data generated in daily life. The focus is on understanding the different types of data, structured versus unstructured data, and the various formats that data can take. This segment lays the groundwork for thinking critically about how data is prepared for exploration and analysis. 2. **Bias, Kredibilitas, Privasi, Etika, dan Akses (Bias, Credibility, Privacy, Ethics, and Access)** This crucial section discusses the importance of ensuring that data used in analysis is free from bias and credible. Learners will explore how to identify types of bias in data and strategies for ensuring data credibility. Additionally, issues relating to open data, data ethics, and the importance of data privacy are discussed, making this an essential area for any aspiring data analyst. 3. **Database: Tempat Data Berada (Database: Where Data Lives)** Understanding databases is critical for any data analyst. This section teaches learners how to access, extract, filter, and sort data from databases. Furthermore, the course delves into metadata, providing insights into the various data types and how analysts employ this knowledge. 4. **Mengatur dan Melindungi Data (Organizing and Protecting Data)** Organizational skills are crucial in data analysis. Learners will cover best practices for keeping data well-organized and secure. This includes file naming conventions that aid in maintaining clarity and order in an analyst's workflow—skills that are valuable in any professional setting. 5. **Opsional: Menjalin Hubungan dengan Komunitas Data (Optional: Building Relationships with the Data Community)** While optional, this section emphasizes the importance of having a robust online presence. Learners are introduced to strategies for managing their online existence and the benefits of networking with other data professionals. This knowledge can be instrumental in securing job opportunities and building a professional brand. **Assessment** The course culminates in a material exam that thoroughly tests the knowledge gained throughout the modules. Participants will be quizzed on terminology and definitions, ethical and privacy considerations, bias identification, and practical skills in using spreadsheets and SQL functions for filtering and sorting data. Additionally, students will demonstrate their ability to secure and organize data effectively using industry best practices. ### Recommendation I highly recommend the "Mempersiapkan Data untuk Eksplorasi" course to anyone interested in starting a career in data analytics. The course successfully combines theoretical knowledge with practical application, making it suitable for beginners and those looking to refine their skills. The structured modules provide an excellent foundation, while the hands-on assignments and assessments ensure that participants can apply what they learn in real-world contexts. With the increasing demand for data analysts in various industries, taking this course not only enhances your resume, but it also builds a strong skill set that can help you successfully navigate the complexities of data analysis. Enroll now on Coursera and take the first step towards a fulfilling career in data analytics!

Syllabus

Tipe dan struktur data

Kita menghasilkan banyak data dalam kehidupan kita sehari-hari. Di bagian materi ini, Anda akan melihat bagaimana kita menghasilkan data dan bagaimana analis memutuskan data mana yang akan dikumpulkan untuk analisis. Anda juga akan belajar tentang data terstruktur dan tidak terstruktur, tipe data, dan format data selagi Anda mulai memikirkan cara menyiapkan data untuk eksplorasi.

Ketika analis data bekerja dengan data, mereka selalu memeriksa bahwa data tidak bias dan kredibel. Pada bagian materi berikut ini, Anda akan belajar bagaimana mengidentifikasi berbagai jenis bias dalam data dan bagaimana memastikan kredibilitas data Anda. Anda juga akan mengeksplorasi open data dan hubungan antara etika data dan privasi data serta pentingnya hubungan tersebut.

Saat menganalisis data, Anda akan mengakses banyak data dari database. Di situlah tempat data berada. Pada materi ini, Anda akan mempelajari semua hal tentang database, termasuk cara mengaksesnya serta mengekstrak, memfilter, dan menyortir data yang ada di dalamnya. Anda juga akan memeriksa metadata untuk menemukan berbagai tipe data dan bagaimana para analis menggunakannya.

Keterampilan organisasi/pengaturan yang baik adalah bagian penting dari sebagian besar jenis pekerjaan, dan analisis data tidaklah berbeda. Di bagian materi ini, Anda akan mempelajari praktik terbaik untuk mengatur data dan menjaganya agar tetap aman. Anda juga akan mempelajari bagaimana para analis menggunakan konvensi penamaan file untuk membantu menjaga pekerjaan mereka tetap teratur.

Memiliki eksistensi online yang kuat dapat membantu para pencari kerja. Pada bagian materi ini, Anda akan mempelajari cara mengelola eksistensi online. Anda juga akan memahami manfaat berjejaring (networking) dengan analis data profesional lainnya.

Persiapkan ujian materi dengan meninjau istilah dan definisi dalam glosarium. Kemudian, tunjukkan pengetahuan Anda tentang pengumpulan data, etika dan privasi, dan bias selama kuis berlangsung. Anda juga akan memiliki kesempatan untuk menerapkan keahlian Anda dengan spreadsheet dan fungsi SQL, serta dalam filtering dan sorting. Terakhir, amankan dan atur data dengan praktik terbaik analitis data.