Data Analyst?

Summary

This video script delves into the comprehensive role of a data analyst beyond mere querying. It emphasizes the importance of data collection, understanding business processes, and domain knowledge. The script outlines the steps from identifying the problem with the marketing team to processing data using tools like Excel, SQL, or Python to find patterns and insights. It highlights the necessity of effective data visualization and communication to present findings and solutions, advocating for continuous learning and curiosity in the field. The video also promotes a mini course on data analysis skills, including Excel, SQL, and Python, offered by the presenter's academy.

Takeaways

• 😀 A data analyst's job is not just about running queries; it involves transforming raw data into actionable insights.
• 🔍 Data analysts are responsible for collecting data, which can be from internal teams like marketing, HR, or sales, or from external sources.
• 🗣️ Communication is key; data analysts should proactively reach out to other teams to understand the data they possess and how it can be utilized.
• 📊 Understanding each data column and variable is crucial for accurate analysis, which requires interaction with the teams that generated the data.
• 📚 Data analysts must have domain knowledge of the business area they are working with to effectively interpret the data and its implications.
• 🛠️ Before analyzing data, it's important to understand the business problem that needs solving, which involves discussions with relevant teams or managers.
• 🔧 Data processing involves using tools like Excel, SQL, or Python, chosen based on the size and complexity of the data set.
• 📈 After processing the data, identifying patterns and trends can lead to solutions, such as determining the best times for marketing promotions.
• 📝 Data analysts should not only be analytical but also creative in presenting their findings and solutions through data visualization or reports.
• 🎤 Strong public speaking and presentation skills are necessary to effectively communicate data insights and recommendations.
• 📚 Continuous learning and curiosity are essential for data analysts to stay updated with different business areas and improve their skills.

Q & A

What is the primary role of a data analyst?

A data analyst's primary role is to process data into insights, which are often presented in the form of data visualizations or reports.

Is the job of a data analyst limited to just querying data?

No, a data analyst's job is not limited to querying data. It includes collecting data, understanding its context, analyzing it to solve specific problems, and presenting findings.

Why is it important for a data analyst to be proactive in collecting data?

It's important because in many companies, especially small to medium-sized ones, data may not be centralized, and analysts need to actively seek out data from various internal and external sources to ensure completeness and relevance for analysis.

What does a data analyst need to understand before starting data analysis?

A data analyst needs to understand the context of the data, including the definitions of each column or variable, the business process or domain knowledge related to the data, and the specific problems or questions the data is intended to address.

Why is domain knowledge important for a data analyst?

Domain knowledge is crucial for a data analyst to correctly interpret the data, understand the business context, and provide meaningful insights and solutions.

How does a data analyst identify the problems they need to solve with the data?

A data analyst identifies problems by communicating with the relevant teams, understanding their challenges, and discussing the issues they face to determine what the data analysis aims to address.

What tools might a data analyst use to process and analyze data?

A data analyst might use tools like Excel for smaller datasets, or SQL and Python for larger, more complex datasets to process and analyze the data.

How should a data analyst present their findings to make them easily understandable?

A data analyst should present their findings using data visualizations or reports, which are designed to make the insights and recommended solutions clear and accessible to the user.

Why is public speaking and presentation skills important for a data analyst?

Public speaking and presentation skills are important for a data analyst to effectively communicate complex data insights and solutions to stakeholders in a clear and engaging manner.

What is the significance of the 'query monkey' term mentioned in the script?

The term 'query monkey' is used to describe someone who only performs data queries without understanding the broader context or purpose of the data analysis, which is not the ideal approach for a data analyst.

What is the Mini Course offered by the speaker for learning data analysis?

The Mini Course mentioned in the script is designed to teach data analysis end-to-end, starting from learning Excel, SQL, and Python, with a focus on practical application in data analysis.

Outlines

00:00

📊 Understanding the Role of a Data Analyst

The first paragraph introduces the role of a data analyst, emphasizing that it is more than just running queries. It involves collecting data, especially in small to medium-sized companies where data may not be extensive or a data engineer may not be available. The data analyst must proactively gather data from various internal sources such as marketing, HR, or sales, and also understand the business processes and domain knowledge related to the data they handle. This includes learning about the purpose of marketing, sales, or other relevant business areas to provide meaningful insights. The paragraph also highlights the importance of identifying the problems that the data analyst aims to solve with their analysis.

05:01

🛠 The Data Analysis Process and Tools

The second paragraph delves into the actual data analysis process, starting with the understanding of the problem at hand. It mentions that data analysts should not rush into analysis but should first comprehend the domain knowledge and the specific issues they are addressing. The paragraph outlines the tools that can be used for data analysis, such as Excel for smaller datasets and SQL or Python for larger ones. It also discusses the importance of identifying patterns and trends in the data, such as the best times for marketing promotions based on historical data. Furthermore, it stresses the need for data analysts to not only analyze data but also to propose solutions, communicate findings effectively using data visualization or reports, and have good public speaking skills to present their insights clearly. The paragraph concludes with a mention of a mini course on data analysis offered by Halotch Academy, which covers learning Excel, SQL, and Python for end-to-end data analysis skills.

Keywords

💡Data Analyst

A data analyst is a professional who collects, processes, and interprets data to provide insights and support decision-making. In the video, the role of a data analyst is discussed in the context of their responsibilities, which extend beyond merely running queries to include gathering data, understanding business processes, and communicating findings. The script mentions that a data analyst must be proactive in collecting data from various teams such as marketing, HR, or sales.

💡Data Collection

Data collection is the process of gathering information from various sources, which is a fundamental task for a data analyst. The script emphasizes the importance of being proactive in this process, especially in smaller companies where data might not be centralized. It gives an example of a data analyst asking teams like marketing or sales if they have data that can be utilized.

💡Data Processing

Data processing involves organizing and manipulating data to make it suitable for analysis. The video script explains that data analysts should not immediately jump into analysis but should first understand the data's context, including the definitions of each column and variable, and the business domain knowledge related to the data.

💡Business Knowledge

Business knowledge refers to the understanding of the industry-specific practices, terminology, and strategies that are relevant to the data being analyzed. In the script, it is mentioned that data analysts are expected to learn and be curious about different business domains, such as marketing or sales, to better interpret the data they work with.

💡Domain Knowledge

Domain knowledge is the specific understanding of a particular area or field that is necessary for a data analyst to correctly interpret data. The video script uses the example of understanding marketing strategies and objectives to illustrate the importance of having domain knowledge in analyzing marketing data effectively.

💡Data Visualization

Data visualization is the graphical representation of information and data, which makes it easier to understand and communicate complex data. The script discusses the importance of using data visualization tools like Excel or Power BI to present insights to stakeholders in a clear and digestible manner.

💡Insights

Insights are the valuable conclusions or findings derived from the analysis of data. In the context of the video, insights are the end goal of a data analyst's work, providing actionable information to help solve business problems, such as determining the best time for marketing promotions.

💡Problem-Solving

Problem-solving is the process of identifying, understanding, and figuring out the solution to a problem. The script highlights that data analysts must first understand the problems faced by different teams, such as the marketing team's challenge of determining the optimal time for promotions, before they can apply data analysis to find solutions.

💡Excel

Excel is a widely used software for creating spreadsheets, performing data analysis, and creating basic data visualizations. The video script mentions Excel as a tool that data analysts can use, especially for smaller datasets, to process and analyze data.

💡SQL

SQL, or Structured Query Language, is a standard language for managing and manipulating relational databases. The script suggests that for larger datasets, data analysts might use SQL to process and analyze the data more efficiently.

💡Python

Python is a versatile programming language that is widely used in data analysis for its powerful libraries and frameworks. The video script implies that Python could be used by data analysts for more complex data processing tasks, especially when dealing with large volumes of data.

Highlights

Data analysts are responsible for processing data into insights, often presented through visualizations or reports.

Data analysts may need to collect data themselves, especially in medium or small-scale companies without dedicated data engineers.

Proactively reaching out to other teams to gather data is crucial for data analysts.

Understanding the context and purpose of the data is essential before analysis.

Data analysts should continuously learn and be curious to understand the domain knowledge relevant to the data they are analyzing.

Identifying the problems or questions that a team has is a key step before data processing.

Data processing should be goal-oriented and informed by domain knowledge.

Data analysts can use tools like Excel, SQL, or Python for data processing depending on the data size and complexity.

Analyzing data to find patterns or trends is a critical part of a data analyst's job.

Data analysts should propose solutions based on the insights gained from data analysis.

Effective communication of data insights and proposed solutions is vital, often using data visualization or reports.

Data visualization should be designed to help users easily understand the insights and recommended actions.

Public speaking and presentation skills are important for data analysts to convey their findings effectively.

The process of data analysis may vary depending on the company and context.

Halotch Academy offers mini-courses covering end-to-end data analysis skills, including Excel, SQL, and Python.

The mini-course on data analysis using Excel focuses on the practical aspects of data processing.

The course is affordable and considered worth the investment for learning data analysis skills.

Transcripts

Hm data analis Hm lumayan banyak juga

longannya tapi apa sih data

analis nanti kerjaannya ngapain ya oke

setelah kemarin kita Ris tentang query

monkey yaitu data analis yang

ngquery-query doang Sekarang kita akan

bahas sebenarnya apa sih kerjaan data

analis seharusnya data analis itu gimana

sih kerjaannya Apakah cuman query-query

doang atauk kan ada yang lain nya kita

akan bahas di sini simpelnya adalah data

Analis adalah orang yang mengolah data

hingga menjadi Insight Inside ini

biasanya kita e presentasikan atau kita

sajikan dalam bentuk visualisasi data

ataupun report nah intinya itu cuman

gimana sih secara detail e prosesnya

data analis itu ngapain aja G

kerjaannya data analis ternyata bertugas

untuk mengumpulkan data juga loh

terutama untuk kalian yang bekerja di

perusahaan-perusahaan yang masih

menengah atau skala kecil biasanya

data-datnya belum besar dan belum ada

data engineer jadi harus kalian sendiri

nih yang mengumpulkan data baik itu dari

internal seperti tim marketing atau HR

atau sales ataupun dari eksternal Jadi

kalian Harus proaktif nih nanya ke

tim-tim lain kira-kira ada data enggak

sih di tim marketing Git kira-kira ada

data enggak sih di tim sales yang bisa

gua manfaatin nah ini penting banget nih

karena kadang-kadang di tim lain Tu

enggak sadar bahwa mereka itu punya data

yang sebenarnya kalau diolah itu penting

banget buat kita sebagai data analis Nah

setelah kalian beres nih ngumpulin data

terus gimana langsung

analisis Oh enggak S kalian dapatin nih

datanya kalian enggak harus langsung

pergi untuk analisis tapi kalian harus

terus berkomunikasi dengan tim yang lain

datanya Seperti apa kalian tanya-tanya

ke tim marketing kalian tanya-tanya ke

tim sales atau yang lainnya sampai

kalian benar-benar mengerti setiap kolom

atau setiap variabel yang dimiliki oleh

setiap data tersebut Contoh nih lu punya

data marketing kalian harus tahu tuh

kolom-kolom atau value-value yang

berkaitan dengan team marketing tersebut

hingga clear nah mudah ngerti nih setiap

kolom-kolomnya setiap row-rowow-nya

terus apakah langsung kita analisis atau

mengolah data Tunggu

dulu sebelum itu kita harus tahu juga

Proses bisnis atau domain knowledge dari

tim tersebut Contoh misalkan kita lagi

bekerja dengan timam marketing Nah kitaa

harus ngerti nih marketing itu apa gu

sebenarnya ngapain aja sih marketing G

sebenarnya Tujuan marketing itu apa gitu

dia tuh ngapain itu dia promosi itu

gimana caranya itu kita harus tahu jadi

data analis sendiri dituntut untuk bisa

selalu belajar dan selalu kurius karena

ketika misalkan kalian berhadapan dengan

tim marketing kalian akan belajar

marketing sedangkan ketika kalian

berhadapan dengan tim sales Kalian juga

harus belajar sales dan juga beberapa

produk yang lainnya misalkan Kalian ada

di menganalisis data retail kalian harus

paham juga terkait produk retail

tersebut nah ini disebut kalian memahami

bisnis knowledge atau domain knowledge

dari data tersebut Nah setelah kalian

kumpulin nih datanya kalian sudah cari

tahu definisi-definisi dari setiap

kolomnya terus resarch juga Gimana

domainledge-nya terkait e data tersebut

selanjutnya

Apa selanjutnya sebelumah data kita

harus tahu dulu sebenarnya apa sih

Masalah dari atau masalah dari suatu

user tersebut misalkan kita lagi bahas

team marketing nih nah kita harus tahu

nih kita harus ngobrol sama team

marketing sebenarnya masalah lu itu apa

gitu lu tuh ada problem apa di tim harus

tahu nih ngobrol misalkan sama manajer

marketingnya atau misalkan sama

teman-teman marketing ya lu ngobrol aja

santai Nah contoh misalkan problemnya

adalah team marketing tuh pengin tahu

sebenarnya Kapan sih waktu yang tepat

untuk bikin

promosi karena kadang promosinya itu

berhasil atau mendapatkan eh e

mendapatkan sales yang besar dan kadang

juga enggak nah mereka Enggak tahu nih

kapan yang berhasil nah di situlah Lu

harus tahu dulu Oh itu problemnya terus

ada lagiah problem yang lain nah lu

kumpulin tuh problem-prblemnya dan

setelah lu kumpulin

problem-prnya baru kita akan solve

dengan cara mengolah data

oke sekarang barulah kita mulai untuk

mengolah data dari proses-proses

sebelumnya nah barulah kita bisa

mengolah data dengan tujuan yang sudah

ditentukan dan juga domain ke knowledge

yang sudah kita mengerti jadi ngolah

datanya Enggak cuman query-query doang

tapi kita benar ngerti nih apa yang kita

akan analisis apa yang masalah yang akan

kita coba solve untuk mengolah datanya

sih itu bebas kalian bisa menggunakan

Excel SQL ataupun Python nah biasanya

kalau misalkan datanya masih kecil

misalkan masih 1000 atau 2000 row kalian

bisa pakai Excel karena itu lebih mudah

tapi kalau misalkan udah lumayan besar

kalian bisa pakai SQL ataupun pyon

ataupun Python Nah di situ baru tuh

Kalian cari tahu misalkan patternnya

kayak gimana alur Kapan promosi market

itu berhasil tuh berdasarkan data gimana

Apakah ketika awal bulan misalkan Apakah

ketika weekend jadi setelah mengolah

data ternyata Berdasarkan data tersebut

kita tahu nih hasilnya Oh ternyata

Biasanya nih promosi yang berhasil itu

adalah ketika weekend dan juga awal

bulan Kita juga harus nguin solusi J

kita gak hanya e pasif setelah mengolah

data apa terus setah itu apa kita harus

solusi nah solusinya dari tim data

adalah kita coba untuk ngakuin marketing

atau promosi lebih baik di setiap

weekend kita gencerin tuh atau di awal

bulan jadi dat juga perah dataapat

insnya harus

tah data faktanya ini solusinya apa Nah

kita harus ajuin nih ke tim

marketing Nah setelah tahu nih eh

datanya Seperti apa atau solusinya

Seperti apa kita harus sampaikan nih ke

team marketing atau ke user data yang

telah kita olah nah gimana sih cara

nyampaininnya biar enak dimengerti itu

adalah menggunakan data visualisasi

ataupun dengan report biasanya nah

tujuannya ingat tujuan dari data

visualisasi ini dibuat adalah untuk

memudahkan si user untuk mengerti apa si

ins dari data tersebut dan juga solusi

yang akan kita sarankan itu itu tujuan

amanya jadi baik pakai Exel atau

misalkan power Bi

atuner leh

ngertiit visualisasi kitait data kita

Nah

dialian harus im public speaking yang

baik gim presentasi yang baik gimana

kalian bisa menyampaikan si data

visualisasi itu terurut atau

misalkanerti misalkan kaliak tiba-tiba

kalian ngjelas solusi kan gak mungkin

kan harus ceritain dulu misalkan ins

datanya

seperti terus turunan insnya Seperti apa

dan akhirnya kalian mengajukan suatuusi

atau kesimpulanah inius

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visualis lebih mengerti dan juga

ee lebih enak dibacanya seperti itu oke

mungkin segitu aja guys dari gua semoga

bermanfaat tapi ini enggak menutup

kemungkinan di perusahaan atau

perusahaan lain berbeda karena

kadang-kadang konteksnya memang berbeda

cuman secara flow secara idealnya kalian

harus melakukan beberapa step ini Jadi

jangan sampai kalian Cuma jadi query

monkey apa sih query monkey cek di video

sebelah Oke mungkin terakhir dari gua

buat kalian yang pengin belajar data

analis halch Academy punya Mini coursese

nah Mini coursese kita udah kita rancang

sebenarnya dari

end to end dari belajar Excel belajar

SQL dan juga Python Nah untuk eh

dekat-dekat ini ketika video ini

di-upload itu kita ada belajar data

analis menggunakan Excel jadi bakal

fokus ke lebih ke data analis gimana

sebenarnya ngolah data eh sebagai data

analis tapi menggunakan Excel Nah kalau

buat kalian bisa Langsung cek di

deskripsi link pendaftaran n ya ya di

sini ada enam temuan jadi dengan harga

r00.000 r00.000an itu masih worth it

menurut gua oke itu aja Dari Gua and see

you in next video

bye Terima kasih telah menonton halotch

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