Understanding Data

Chapter 3 describes the sources and nature of data in some detail: how data is generated and what affects data quality. Data may originate from transaction systems, sensors, social media sites, or crowdsourcing. It comes in different forms, such as structured and unstructured data; it may be updated in real time or periodically and may have variable accuracy. The nature of the source, whether it be a person or device, is relevant to understand the type of processing and analysis that will be conducted. Also, the method of collection, whether it be through survey, sensor, or third-party aggregator, affects the completeness and representativeness of the data, which in turn impacts the reliability of any insights drawn from it.


Chapter 4 looks into the destination of data-data pipelines, data warehousing, and modern data infrastructure. Data pipelines are the frameworks that enable raw data to flow from its source to its destination, often requiring multistage transformations, cleaning, and enrichment on the way. This process ensures that the data becomes usable and aligned with business goals. Afterwards, the refined data is sent for storage, usually to a data warehouse, where it gets collected in one place for querying and analysis. It also highlights that using modern infrastructure such as cloud storage and distributed computing can achieve great scale for data operations and can manage high volumes efficiently.


A key skill in working with data is the use of SQL, or Structured Query Language. SQL allows users to interact with relational databases, extracting information and manipulating data in everything from simple retrievals to complex joins and aggregations. The ability to build and optimize data queries, which are foundational to analyzing and interpreting large datasets, requires mastery in SQL. This chapter proceeds hands-on with SQL to take one through exercises that draw out the practical skills in querying databases. With the ever-increasing reliance on data-driven decision-making in organizations, good use of SQL becomes an essential tool in both the data analyst's and data engineer's toolkit.




Comments

Post a Comment

Popular posts from this blog

Week 1 Intro

Image
   Hello, my name is Mariana Meraz, and I am currently a senior at Benedictine University in Mesa, majoring in Accounting. In addition to my academic pursuits, I have the honor of serving as the president of the Rotaract Club, collaborating closely with the Rotary Club of Mesa. Outside of my studies, I am deeply committed to giving back to the community. I actively volunteer for various projects and am currently involved with an organization that helps low-income families file their taxes for free. I am passionate about using my skills and time to make a positive impact on those in need.
Read more

Using Google Colab for Hands-on Python

Image
This chapter discussed Google Colab, which is a cloud-based platform where one can write and execute Python code without installation on their local machine. While this may sound more relevant to programming-related fields, it has tremendous benefits for accountants too. After learning accounting, Google Colab and Python can provide a variety of advantages. The greatest benefit is probably the ability to analyze and automate. Accounting is increasingly data-driven in decision-making, and Python is an incredibly powerful tool for handling big data. With Google Colab, accountants can use Python to financial modeling, trend analysis, and automating routine tasks such as reconciliations and report generation. Another advantage of Google Colab is its cloud platform, which facilitates seamless collaboration. Since files are stored in Google Drive, accountants and financial analysts can collaborate over reports and financial models in real-time. This is particularly useful in audit practices,...
Read more

AI Career-Oriented Projects: Boost Your Resume and Stand Out

Image
     Artificial Intelligence is transforming businesses, and having AI skills can help you become a job market standout. Either as a student, a career professional looking to upskill, or just an AI beginner, completing an AI project can help you gain experience and show your abilities to potential employers.         For my final project, I have chosen to design an AI Tutor for Coding and Language Learning. Drawing from my own experience and past courses, I have often found it difficult to understand complex coding concepts and pick up new languages. An AI tutor would have been a big help to me by providing instant feedback, personalized learning pathways, and interactive exercises. This project will utilize AI to assist students through coding explanations, debugging support, and language practice, thus making learning easier and interactive. AI Resume & Cover Letter Analyzer      Employers use AI to scan resumes, so why not use...
Read more