Knowledge Hut

OCTOBER 30, 2023

Soft Skills Analytical Skills: Strong analytical and problem-solving abilities to interpret data, identify trends, and provide actionable insights. The capacity to translate business requirements into data visualization solutions. Proficiency in SQL for data querying and manipulation, especially when dealing with relational databases.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

ProjectPro

DECEMBER 22, 2016

The various steps involved in the data analysis process include – Data Exploration – Having identified the business problem, a data analyst has to go through the data provided by the client to analyse the root cause of the problem. 5) What is data cleansing?

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

DataKitchen

SEPTEMBER 20, 2021

As discussed earlier, data professionals spend over half of their time on operational execution. Think of your data operations workflows as a series of pipeline steps. For example, data cleansing, ETL, running a model, or even provisioning cloud infrastructure.

Data Pipeline 98

Data Pipeline Process Data Cleanse Architecture 98

Knowledge Hut

SEPTEMBER 26, 2023

Adding slicers and filters to allow users to control data views. 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. Creating bookmarks to save and recall specific dashboard views.

BI 52

BI Business Intelligence Raw Data Data Analysis 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 Raw Data 52

U-Next

SEPTEMBER 9, 2022

An analytical mindset, a solid statistical foundation, and solid knowledge of data structures and machine learning techniques are essential qualifications for a Data Scientist. They should be proficient in Python or R and at ease handling huge data sets.

Data Science 40

Data Science Computer Science Machine Learning Hadoop 40

ProjectPro

AUGUST 24, 2021

This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. There are three stages in this real-world data engineering project. Data ingestion: In this stage, you get data from Yelp and push the data to Azure Data lake using DataFactory.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2023

Big Data Architect Interview Questions and Answers Following are the interview questions for big data architects that will help you ace your next job interview. Explain the data preparation process. Data preparation is one of the essential steps in a big data project. Steps for Data preparation.

Big Data 52

Big Data Hadoop Relational Database AWS 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

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52