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Ini adalah materi ketiga dalam program Sertifikat Analitik Data Google (Google Data Analytics Certificate). Materi ini akan membekali Anda dengan keterampilan yang Anda butuhkan untuk melamar pekerjaan analis data tingkat pemula. Selagi Anda terus membangun pemahaman tentang topik-topik pada dua materi pertama, Anda juga akan diperkenalkan dengan topik baru yang akan membantu Anda mendapatkan keterampilan praktis analitik data. Anda akan mempelajari cara menggunakan alat seperti spreadsheet dan SQL untuk mengekstrak dan menggunakan data yang tepat untuk tujuan Anda dan cara mengatur dan melindungi data Anda. Para analis data Google akan mengajarkan dan memberi tahu Anda berbagai cara untuk menyelesaikan tugas umum analis data dengan menggunakan peralatan dan sumber daya terbaik.

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Ini adalah materi ketiga dalam program Sertifikat Analitik Data Google (Google Data Analytics Certificate). Materi ini akan membekali Anda dengan keterampilan yang Anda butuhkan untuk melamar pekerjaan analis data tingkat pemula. Selagi Anda terus membangun pemahaman tentang topik-topik pada dua materi pertama, Anda juga akan diperkenalkan dengan topik baru yang akan membantu Anda mendapatkan keterampilan praktis analitik data. Anda akan mempelajari cara menggunakan alat seperti spreadsheet dan SQL untuk mengekstrak dan menggunakan data yang tepat untuk tujuan Anda dan cara mengatur dan melindungi data Anda. Para analis data Google akan mengajarkan dan memberi tahu Anda berbagai cara untuk menyelesaikan tugas umum analis data dengan menggunakan peralatan dan sumber daya terbaik.

Peserta didik yang menyelesaikan program sertifikasi ini akan memiliki bekal yang cukup untuk melamar kerja sebagai analis data tingkat pemula. Tidak membutuhkan pengalaman apa pun.

Di akhir materi ini, Anda akan:

- Mencari tahu bagaimana analis memutuskan data mana yang akan dikumpulkan untuk analisis.

- Mempelajari tentang data terstruktur dan tidak terstruktur, tipe data, dan format data.

- Mengetahui cara mengidentifikasi berbagai jenis bias dalam data untuk membantu memastikan kredibilitas data.

- Mengeksplorasi bagaimana analis menggunakan spreadsheet dan SQL dengan database dan dataset.

- Memeriksa open data dan hubungan antara dan pentingnya etika data dan privasi data.

- Mendapatkan pemahaman tentang cara mengakses database dan mengekstrak, menyaring, dan mengurutkan data yang ada di sana.

- Mempelajari praktik terbaik untuk mengatur data dan menjaganya agar tetap aman.

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What's inside

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.
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Bias, kredibilitas, privasi, etika, dan akses
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.
Database: Tempat data berada
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.
Mengatur dan melindungi data
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.
Opsional: Menjalin hubungan dengan komunitas data
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.
*Ujian Materi*
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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Melatih keterampilan yang dibutuhkan untuk melamar pekerjaan analis data tingkat pemula
Tidak memerlukan pengalaman sebelumnya
Mempersiapkan peserta didik untuk pekerjaan sebagai analis data tingkat pemula

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Save Mempersiapkan Data untuk Eksplorasi to your list so you can find it easily later:
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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Mempersiapkan Data untuk Eksplorasi with these activities:
Kompilasi Catatan dan Materi
Mengatur catatan dan materi Anda akan membantu Anda tetap teratur dan memfasilitasi peninjauan di kemudian hari.
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  • Kumpulkan semua catatan, materi kuliah, dan tugas yang terkait dengan kursus ini.
  • Atur materi ke dalam folder atau sistem yang mudah diakses.
  • Tinjau materi yang dikompilasi secara rutin untuk memperkuat pembelajaran.
Tinjau Teknik Spreadsheet
Tinjau teknik dasar spreadsheet untuk mempersiapkan diri menghadapi topik analisis data lanjutan.
Browse courses on Spreadsheet
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  • Pelajari fungsi dan rumus dasar spreadsheet.
  • Berlatih membuat dan memformat tabel dan grafik.
  • Tinjau fitur pengurutan dan pemfilteran.
Diskusikan Konsep dengan Teman Sebaya
Berdiskusi dengan teman sebaya akan membantu Anda mengklarifikasi konsep, mendapatkan perspektif yang berbeda, dan mengidentifikasi area yang perlu ditingkatkan.
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  • Temukan teman sebaya yang bersedia belajar bersama.
  • Jadwalkan waktu untuk mendiskusikan topik atau konsep tertentu.
  • Bantu satu sama lain memahami materi dan kerjakan soal bersama-sama.
Two other activities
Expand to see all activities and additional details
Show all five activities
Latihan Menggunakan Spreadsheet
Berlatih menggunakan spreadsheet akan meningkatkan keterampilan Anda dalam mengelola dan menganalisis data, yang penting untuk analis data.
Browse courses on Spreadsheet
Show steps
  • Buka spreadsheet dan masukkan beberapa data.
  • Terapkan fungsi dan rumus untuk menganalisis data.
  • Buat bagan dan grafik untuk memvisualisasikan data.
Practice SQL data manipulation
Membiasakan diri dengan sintaks SQL melalui latihan akan meningkatkan pemahaman Anda tentang bagaimana mengekstrak, memfilter, dan mengurutkan data.
Browse courses on SQL
Show steps
  • Carilah soal latihan SQL secara online
  • Gunakan platform latihan SQL interaktif
  • Coba selesaikan tantangan SQL harian

Career center

Learners who complete Mempersiapkan Data untuk Eksplorasi will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst's responsibilities are to analyze data with the goal of extracting meaningful insights. To be successful in this role, you must first understand how to collect data and evaluate its credibility, which is covered in this course. As a Data Analyst, you will rely on spreadsheets and SQL to identify trends that may not be obvious without analysis.
Database Administrator
In the role of a Database Administrator, you will handle the installation, configuration, and maintenance of databases. It is a technical role that contributes to the efficiency of an organization. This course provides essential knowledge on how to organize and protect data through the use of best practices.
Data Scientist
Data Scientists combine programming skills with their knowledge of mathematics and statistics. They are responsible for developing models and algorithms that predict future trends and outcomes. This course provides the foundation needed to understand bias and data credibility. This is especially important for Data Scientists, who must be able to rely on the data they are using.
Statistician
Statisticians collect, analyze, and interpret data. Because of the volume of data that is now available, Statisticians are needed to help businesses and organizations use data to make more informed decisions. This course may be helpful as it provides instruction on data structure and data quality.
Data Engineer
Data Engineers build, maintain, and manage data storage and processing systems. They work to ensure that these systems are efficient and reliable. By taking this course, you can gain a better understanding of database structure, which is an important component of data management.
Business Analyst
A Business Analyst's role is to analyze an organization's operations and help to improve efficiency. By understanding the types and formats of data, and how to identify bias, you can make well-reasoned recommendations that are supported by data.
Market Researcher
Market Researchers study market conditions, analyze data, and identify trends. This course may be helpful as it covers the topic of data credibility, which is critical to the success of a Market Researcher.
Software Engineer
Software Engineers design, develop, test, and maintain software systems. They rely on data to evaluate a system's performance. This course may be helpful for Software Engineers by providing an understanding of data types.
Financial Analyst
Financial Analysts use data to evaluate the financial performance of companies. They make recommendations on how to invest money and manage risk. This course provides a solid foundation for data analysis and may be helpful to a Financial Analyst who is new to the field.
Risk Analyst
Risk Analysts help organizations identify and manage risks. They use data to evaluate the likelihood and impact of potential risks. This course may be helpful for Risk Analysts as it covers techniques for ensuring data credibility.
Quality Assurance Analyst
Quality Assurance Analysts test and evaluate software and other products to ensure they meet quality standards. They use data to identify and track defects. This course may be helpful for Quality Assurance Analysts as it covers techniques for organizing and protecting data.
Information Security Analyst
Information Security Analysts protect organizations from cyber attacks and other security threats. They use data to identify and mitigate risks. This course may be helpful for Information Security Analysts as it covers techniques for protecting data from unauthorized access.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve business problems. They use data to develop models and make recommendations. Understanding the types and structure of data is a helpful foundation for success in this role, which you can learn in this course.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They use data to develop models that predict future events. This course may be helpful for Actuaries as it provides a foundation for evaluating the credibility of data.
Auditor
Auditors examine financial records to ensure that they are accurate and compliant with regulations. They use data to identify errors and fraud. This course may be helpful for Auditors as it covers techniques for auditing data and ensuring its integrity.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Mempersiapkan Data untuk Eksplorasi.
Provides a comprehensive guide to data preparation, covering topics such as data cleaning, transformation, and feature engineering. It valuable resource for anyone who wants to learn more about the process of preparing data for analysis.
Provides a comprehensive introduction to statistical learning, which powerful tool for understanding data and making predictions. It valuable resource for anyone who wants to learn more about statistical learning, or who wants to use statistical learning to solve problems.
Provides a comprehensive introduction to statistical learning, with a focus on applications in R. It valuable resource for anyone who wants to learn more about statistical learning, or who wants to use statistical learning to solve problems in R.
Provides a comprehensive introduction to machine learning, with a focus on the probabilistic perspective. It valuable resource for anyone who wants to learn more about machine learning, or who wants to use machine learning to solve problems.
Provides a comprehensive introduction to pattern recognition and machine learning. It valuable resource for anyone who wants to learn more about these topics, or who wants to use them to solve problems.
Provides a comprehensive introduction to deep learning, which powerful new approach to machine learning. It valuable resource for anyone who wants to learn more about deep learning, or who wants to use deep learning to solve problems.
Provides a practical introduction to data science for business professionals. It covers topics such as data mining, machine learning, and data visualization. It valuable resource for anyone who wants to learn more about how data can be used to improve business decision-making.
Provides a comprehensive introduction to data mining, which powerful tool for extracting knowledge from data. It valuable resource for anyone who wants to learn more about data mining, or who wants to use data mining to solve problems.
Provides a comprehensive guide to dimensional modeling, which technique for organizing data in a way that makes it easy to analyze. It valuable resource for anyone who wants to learn more about data warehousing and data analysis.
Provides a comprehensive guide to using Python for data analysis. It covers topics such as data cleaning, data manipulation, and data visualization. It valuable resource for anyone who wants to learn more about using Python for data analysis.
Provides a clear and concise introduction to artificial intelligence, which rapidly growing field that is transforming the world around us. It valuable resource for anyone who wants to learn more about artificial intelligence, or who wants to use artificial intelligence to solve problems.
Provides a clear and concise introduction to machine learning, which powerful tool for automating tasks and making predictions. It valuable resource for anyone who wants to learn more about machine learning, or who wants to use machine learning to solve problems.

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