Seeing the Huge Opportunity for Data Technician Needs, Skystar Ventures Launches DQLab

One of the digital trends brought about by the industrial revolution 4.0 is data optimization -- in the sense of trying to take advantage of existing data in the business to convert it into knowledge. It's no wonder that nowadays almost every company needs a data team, from analysts, technicians, to programmers. Seeing this opportunity, DQLab is here to provide a forum in the form of a learning channel about data. Its programs provide comprehensive teaching on data management with industry case studies.

To find out more about the program DQLab, DailySocial have talked to Yovita Surianto as Program Director. He defines DQLab as a learning program data science which is packaged with project-based practical and applicative methods. This approach is taken to bring the real experience and complexity related to data processing in companies, especially in Indonesia. This program was initiated by Multimedia Nusantara University (in this case through Skystar Ventures) and PHI-Integration.

"Our vision is to create data talent who can contribute appropriately to the companies they work for. With the creation of many data talents who can provide impact, will create a strong data ecosystem towards a better Indonesia data-driven"explained Yovita.

The need for data talent is still very large

Citing the results of research by Microsoft and IDC published in early 2018, out of 79% of companies in Indonesia that are currently carrying out the digital transformation process, only 7% have a comprehensive digital strategy. In a previous article, DailySocial also discussed about digital transformation, two aspects are directly related to the data, namely data-driven strategy and data analytics. Industry 4.0, which leads to digitalization and automation, requires industry players to quickly adapt to changes.

"The number of technical education programs in Indonesia to build digital transformation talent is the right initiative. Education in the field of data science structured and appropriate can help optimize the processing and analysis of data. We believe, exposure to a variety of case studies and data handling will help data practitioners understand, not just use tools but sharpening problemsolved and analytical skills," continued Yovita.

The current condition is that the company has a lot of data, along with computerization in various segments. Unfortunately, according to Yovita, until now there are still many problems in the data so that it is not feasible to be processed into useful knowledge and causes the results of the analysis to be less reliable. Issues such as structure to data redundancy are still common. Meanwhile, in the midst of global competition, companies need to be agile and make decisions quickly, of course, not only based on assumptions, but also measured analysis.

"Proper data processing can bring up insight interesting to help decision making for businesses. Examples of case studies: to determine the right product package and have an impact on sales, carry out a consumer segmentation process to help targeted marketing activities, determine variables to predict credit scoring, and many others," explained Yovita.

DQLab with a community based approach

Currently, there are many educational programs that specifically teach about data science. Besides DQLab, there are also algorithm which specifically organizes integrated workshops on data science. The community-based approach is considered relevant by DQLab. With this approach, DQLab connects various parties, ranging from industry, practitioners, and educators; to complement each other. PHI-Integration as a strategic partner of DQLab is a data consultant in Indonesia. PHI-Integration focuses on content and platform development.

"The DQLab program is open to the public. We are currently working with several companies to provide recommendations talent data that meet the criteria. To provide an understanding of the process and proper data processing techniques, we periodically conduct case review sessions inviting data experts in the industry," concluded Yovita.

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Also read a series of articles on data science from DailySocial:

1. Part 1 – Basic Data Science
2. Part 2 – Big Data
3. Part 3 – Business intelligence
4. Part 4 – Machine Learning