Tag: Data Science
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Standing Firm on Professional Integrity: The Crucial Role of Data Scientists in Data Warehousing and Governance
In the realm of data science, maintaining professional integrity is not just a matter of ethics; it’s a cornerstone of effective and meaningful work. Recently, I encountered a situation during a data warehouse project that highlighted the importance of this principle. I authored a “Data Gap Analysis Report,” where I identified several internal data errors…
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Challenges and Strategies for Improving Efficiency in Data Science Project Teams
In today’s data-driven world, data science projects are gaining increasing attention. However, despite the high technical expertise of many team members, inefficiency often plagues project teams, turning them into a disorganized group. This inefficiency not only delays project timelines but also potentially impacts the final outcomes. This article will discuss common issues within data science…
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Journey to Becoming a Data Scientist: A Comprehensive Guide 2023
Introduction: In today’s data-driven world, the role of a data scientist has gained immense significance. Data scientists play a pivotal role in extracting valuable insights from vast amounts of data, driving business decisions, and solving complex problems across various industries. If you aspire to become a data scientist, this article provides a comprehensive guide to…
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5-year Strategic Plan on Data Science Development
This guideline is based on my personal experiences in tens of data analytics & data science projects and consulting works for the last decade. It should be fit for different organizations including corporations, non-profit organizations and institutions. Here is my suggestions on possible actions throughout a 5-year periods: Year 1: Building the Foundation…
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Different Stages in Data Science Team Building
In general, there are 3 stages of building a data science team. Early Stage Mid Stage Late Stage (Mature Stage) For each stage, the team structure of a data science team should be different in order to meet the needs within the business or organization. Organizational Models Meanwhile, there are 3 different types of Organizational…
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Five Ways to Build a Data Science Team for your Organization
As a data science consultant for years, I would like to share my viewpoints and experiences of developing the capability for a data science team for any organization. (NOTE: this article is aimed to share building data science for general business. However, it is not for helping you to build a Data Science consultancy or…
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Bookshelf for a Data Scientist
As a data scientist, reading book is a daily activity and most of my skills are built from reading. However, I am always reading different types of books outside the data science tools and technology. I would like to share some of the books recommended across different areas. Methodology When doing Data Science, many…
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Data Science / Analytics – Best Practices
Many organizations and people are just focused on technology during the implementation of Big Data and/or Data Analytics. However, you should have the same predictive analytics result for the same algorithm no matter it is the programming code being written in SAS, R or Python. The truth is that the proper methodology is far more…
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Advanced Data Analytics with Free Tools
In the field of Data Science, there are lots of great tools without charging a penny. Data Analytic never requires software tools with high price and the analytic result should be the same either using SAS Data Miner or your own R code. As a data science consulting company, our teams are always using free…
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Discovering Insights from your Data
Big data and data science have been discussed for many years. However, there are lots of failed cases of implementation around the world. With the digitalization, it is no longer difficult to collect data but some organizations are now facing the new problem of drowning in a sea of data. In this article, I would…