Knowledge Hut

JUNE 16, 2023

Data preparation: Because of flaws, redundancy, missing numbers, and other issues, data gathered from numerous sources is always in a raw format. Communication: Proficient communicators are a must for data analysts. Additionally, data analysts should be able to manage multiple projects at once and work well in teams.

Programming Language 52

Programming Language Data Science Data Analytics Cloud Computing 52

Knowledge Hut

JUNE 28, 2023

Focus Exploration and discovery of hidden patterns and trends in data. Reporting, querying, and analyzing structured data to generate actionable insights. Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake Machine Learning BI 64

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

AltexSoft

DECEMBER 15, 2021

Namely, AutoML takes care of routine operations within data preparation, feature extraction, model optimization during the training process, and model selection. In the meantime, we’ll focus on AutoML which drives a considerable part of the MLOps cycle, from data preparation to model validation and getting it ready for deployment.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. The end of a data block points to the location of the next chunk of data blocks.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Knowledge Hut

SEPTEMBER 26, 2023

Workspace and Libraries: Databricks provides a centralized workspace for managing resources, libraries, and data. It also offers a library system for managing dependencies and sharing code across different notebooks and projects. Databricks, on the other hand, offer a broader spectrum of data processing capabilities.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

ProjectPro

SEPTEMBER 30, 2014

Hadoop’s significance in data warehousing is progressing rapidly as a transitory platform for extract, transform, and load (ETL) processing. Mention about ETL and eyes glaze over Hadoop as a logical platform for data preparation and transformation as it allows them to manage huge volume, variety, and velocity of data flawlessly.

Hadoop 52

Hadoop ETL Tools Unstructured Data ETL System 52

ProjectPro

JANUARY 31, 2022

Snowflake Features that Make Data Science Easier Building Data Applications with Snowflake Data Warehouse Snowflake Data Warehouse Architecture How Does Snowflake Store Data Internally? Let us take a look at the unique features of Snowflake that make it better than other data warehousing platforms.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

APRIL 25, 2023

Power BI Power BI is a cloud-based business analytics service that allows data engineers to visualize and analyze data from different sources. It provides a suite of tools for data preparation, modeling, and visualization, as well as collaboration and sharing.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

ProjectPro

APRIL 27, 2016

In case of big data projects that have a limited scope and are monitored by skilled teams –this is not a concern. However, as the big data projects grow within an organization, there is a need to effectively operationalize these systems and maintain them. It is difficult to manage n-stage jobs with Hadoop MapReduce.

Hadoop 40

Hadoop Big Data Technology Kafka 40

ProjectPro

JANUARY 19, 2022

Azure Data Engineers Jobs - The Demand Azure Data Engineer Salary Azure Data Engineer Skills What does an Azure Data Engineer Do? Data is an organization's most valuable asset, so ensuring it can be accessed quickly and securely should be a primary concern. The use of data has risen significantly in recent years.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

Knowledge Hut

APRIL 25, 2024

These technologies are necessary for data scientists to speed up and increase the efficiency of the process. The main features of big data analytics are: 1. Data wrangling and Preparation The idea of Data Preparation procedures conducted once during the project and performed before using any iterative model.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Rockset

OCTOBER 4, 2022

Rockset was started in 2016 to meet the needs of developers building real-time data applications. Rockset leverages RocksDB, a high-performance key-value store, started as an open-source project at Facebook around 2010 and based on earlier work done at Google. Flink, Kafka and MySQL.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Edureka

JULY 4, 2024

On the other hand, thanks to the Spark component, you can perform data preparation, data engineering, ETL, and machine learning tasks using industry-standard Apache Spark. With Databricks, you can simplify DevOps tasks for data teams. What Is Azure Databricks? Databricks, on the other hand, takes a more modular approach.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

ProjectPro

MAY 20, 2015

It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Table of Contents What is a Big Data Project?

Big Data 52

Big Data Coding Project Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle. With Tableau, which focuses on big data visualization , you can create scatter plots, histograms, bar, line, and pie charts.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

ProjectPro

DECEMBER 10, 2021

Where can I find Azure projects/project ideas to enhance my skills? Every cloud service project contains a cscfg file, essentially a cloud service configuration file generated by the cspack tool. Learn more about real-world big data applications with unique examples of big data projects.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

OCTOBER 20, 2021

If you are unsure, be vocal about your thought process and the way you are thinking – take inspiration from the examples below and explain the answer to the interviewer through your learnings and experiences from data science and machine learning projects. How future-proof are the project and the platform?

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

Edureka

JANUARY 29, 2025

Key steps include: Identify the location of the data e.g., Excel files, databases, cloud services, or web APIs, and confirm accessibility and permissions. Data Sources Identification: Ensure that the data is properly formatted (for instance, in tables) and does not contain erroneous values such as nulls or duplicates.

BI 52

BI Datasets Certification Data Analysis 52