Knowledge Hut

JANUARY 25, 2024

Let's dive into the top data cleaning techniques and best practices for the future – no mess, no fuss, just pure data goodness! What is Data Cleaning? It involves removing or correcting incorrect, corrupted, improperly formatted, duplicate, or incomplete data. Why Is Data Cleaning So Important?

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Knowledge Hut

OCTOBER 30, 2023

Data Visualization: Assist in selecting appropriate visualizations for data presentation and formatting visuals for clarity and aesthetics. Data Analysis: Perform basic data analysis and calculations using DAX functions under the guidance of senior team members.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

RandomTrees

FEBRUARY 6, 2024

Transformation: Shaping Data for the Future: LLMs facilitate standardizing date formats with precision and translation of complex organizational structures into logical database designs, streamline the definition of business rules, automate data cleansing, and propose the inclusion of external data for a more complete analytical view.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

SEPTEMBER 26, 2023

Data Preparation and Transformation Skills Preparing the raw data into the right structure and format is the primary and most important step in data analysis. By understanding how to cleanse, organize, and calculate data, you can ensure that your data is accurate and reliable.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Knowledge Hut

FEBRUARY 1, 2024

You cannot expect your analysis to be accurate unless you are sure that the data on which you have performed the analysis is free from any kind of incorrectness. Data cleaning in data science plays a pivotal role in your analysis. The real-world data is messy.

Data Science 52

Data Science Process Data Cleanse Datasets 52

Knowledge Hut

JANUARY 30, 2024

Whether it's aggregating customer interactions, analyzing historical sales trends, or processing real-time sensor data, data extraction initiates the process. Utilizes structured data or datasets that may have already undergone extraction and preparation. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

NOVEMBER 27, 2023

Class-label the observations This consists of arranging the data by categorizing or labelling data points to the appropriate data type such as numerical, or categorical data. Data cleansing / Data scrubbing Dealing with incongruous data, like misspelled categories or missing values.

Data Science 52

Data Science Datasets Machine Learning Portfolio 52