Knowledge Hut

JANUARY 25, 2024

Data cleaning is like ensuring that the ingredients in a recipe are fresh and accurate; otherwise, the final dish won't turn out as expected. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making. Let's explore these essential tools.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

ProjectPro

JANUARY 24, 2023

Time-saving: SageMaker automates many of the tasks, by creating a pipeline starting from data preparation and ML model training, which saves time and resources. Data Flow – A data flow allows you to specify a series of steps for preparing data for machine learning.

Building 52

Building Algorithm Machine Learning AWS 52

Monte Carlo

MAY 25, 2023

Data orchestration is the process of gathering siloed data from various locations across the company, organizing it into a consistent, usable format, and activating it for use by data analysis tools. Some of the value companies can generate from data orchestration tools include: Faster time-to-insights.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

Knowledge Hut

DECEMBER 26, 2023

With the help of the company's "augmented analytics," you can ask natural-language inquiries and receive informative responses while also applying thoughtful data preparation. Some of the best features of oracle analytics cloud are augmented analytics, data discovery, and natural language processing.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

ProjectPro

AUGUST 24, 2021

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. The second stage is data preparation. Here data cleaning and analysis happens using Databricks.

Data Engineer 52

Data Engineer Data Engineering Coding Project 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. Name some data analysis tools that you have worked with.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52