Bringing the Power of Data to Your Business

  • Business
  • July 30, 2021
Bringing the Power of Data to Your Business
Currently, many businesses, especially tech companies, are driven by data. They are using data and analytics to effectively identify their customers’ behaviors, plan their marketing strategies, and run their operations.

On 30 June 2021, True Digital Park organized an online discussion called Tech Master Talk: Bringing the Power of Data to Your Business powered by LSEG (London Stock Exchange Group) to discuss how data can be used to help businesses perform better by talking to 3 speakers from LSEG (London Stock Exchange Group) and LINE MAN Wongnai.


  • Sakwannueng Trakoolshoke-satian (Champ), Lead Data Scientist, LSEG (London Stock Exchange Group)  
  • Chusana Nuntanart (Dew), Senior Data Scientist, LSEG (London Stock Exchange Group)  
  • Manussanun Buranachokphaisan (Kaew), Senior Data Engineer, LINE MAN Wongnai


Here are some useful information companies can take to transform your business into a data-driven business.


Data analytics lifecycle recommended for businesses 


  1. Understand the business: You need to understand what your business does and what data you need. Then start asking questions and goals on how to use data for your organization. For example, sales and marketing are focused on sales, but customer service is focused on customer satisfaction.
  2. Data Collection: Consider what kind of data you need in order to answer your questions and reach your goals. Collect the needed data and store it securely. If that set of data is insufficient to understand your users, find out what more you can collect.
  3. Data Preparation or Data Cleaning: If your data is in an inaccurate format, clean the data before using. In this process it may take a lot of time.
  4. Data Exploration: Exploring and looking at the data trend. For example, the E-commerce business would look to analyze trends from transactions daily/ weekly/ monthly/ quarterly/ yearly.
  5. Data Analytics: This step is advanced analytics. It is data science. Using statistics, data scientists can find out insights of the data then develop a model for machine learning. Some companies combine steps 4 and 5 together.
  6. Visualization: To present data in a visual form such as dashboard, heatmap, and graph, it is important to communicate through proper size, colour, and form.


Job positions of people working with data analytics lifecycle include:

  1. Business Analyst (BA)
  2. Data Engineer
  3. Data Analyst 
  4. Business Intelligence (BI)

Recommended tools for effective data management

  • For data engineer: MySQL and Python 
  • For data Scientist: Python (there is a library such as Pandas, NumPy)
  • For business Intelligence: Tableau, Power BI, Excel
  • For anyone in the organization: Basic tools such as Microsoft Access and Microsoft Excel to create database and visualisation


Ms. Manussanun, Senior Data Engineer from LINE MAN Wongnai, says that her company also uses cloud service platforms from Google Cloud and AWS to help set up a database within the organization.


Companies have to start asking 2 questions to help planning and managing fundamental data within the organization:

  1. How to store the data?
  2. How to collect the data?


In the first stage, there are 2 positions that are needed in data-driven businesses: 

  • Data Engineer
  • Business Intelligence or Data Analyst


In the working process, the data engineer will create a data platform and data pipelines to put data in the correct format, then send it to business intelligence (BI) and apply for visualization or dashboard. 


Once the company has begun to see the benefits of the steps above, the company can develop the data into insights and hire data scientists into the team later.


Challenges in data science include:

  • Data Quality: Some data has to be cleaned before using
  • Data Literacy: Executives and team members sometimes lack understanding or do not see the importance of data collection and analyzation; therefore data engineer or data scientist must show them how beneficial data can offer and get everyone on the same page


Mr. Chusana, Senior Data Scientist of LSEG, said the accuracy of the data is very important. Therefore, the company should always recheck data and try to avoid making mistakes.


Nowadays, data science has become a popular career because it helps support the company by using machine learning. After analysis, the results can provide more accurate directions for the companies to reach their goals than having the company relying on directions from top executives. 


If you are looking to change your career, our speaker recommends upskilling and reskilling by learning more about statistics and programming such as MySQL, Python, Tableau, Microsoft Access, and Excel.



True Digital Park is offering useful talks and events in our community events page, please check them out:


True Digital Park—Southeast Asia's largest tech and startup hub located in the heart of Bangkok CyberTech District.


  • Business
  • Data

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