Category: Big Data
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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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The Four Pillars of a Successful Data Scientist: Logical Thinking, Hunger to Learn, Passion to Implement, and Communication Skills
In today’s data-driven world, the role of a data scientist is both crucial and multifaceted. Success in this field requires a blend of various skills and attributes. While technical proficiency and domain knowledge are important, four key elements stand out as the foundation for a successful data scientist: logical thinking, an insatiable hunger to learn…
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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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Introducing Popular ETL Tool
As a person working in the data science industry for years, I have experienced with 6 different ETL tools for project implementations. For handling a new tool, I think it is likely for 3 working days to pick up the basic skills for implementation. Here’s an introduction to several popular ETL (Extract, Transform, Load) tools…
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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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Importance of Real-time Data Analytics
Real-time (or better say near real-time) analytics make sense of all the real-time data that passing around an organization. Once a business is able to analyze data in real-time, they can generate insights during data streaming instead of storing and analyzing it in batches. Traditionally, data analysis happens once the data has been captured and…
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Importance of Primary Key
I have been working with relational database, NoSQL database and Hadoop HBase for years mainly for storing data for analysis. There is a fundamental problem for people still overlooking the importance of primary key in a table. In this article, I would like to go through the detailed information about primary key such as: definition,…
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Career Opportunity
My team (SDI) is hiring the position of Assistant Data Engineer (trainee) based in Hong Kong. It is an opportunity to develop your data science career. Our client includes: Fortune 500 Government Departments Listed Corporations Statutory Bodies and … many more Please check the job ads: LinkedIn: https://www.linkedin.com/jobs/view/122773078/ WWW: https://smartdatainstitute.com/jobs








