Data Analyst?
Summary
TLDRThis 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
📊 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.
🛠 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.
Mindmap
Keywords
💡Data Analyst
💡Data Collection
💡Data Processing
💡Business Knowledge
💡Domain Knowledge
💡Data Visualization
💡Insights
💡Problem-Solving
💡Excel
💡SQL
💡Python
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
d
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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