Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

JUNE 20, 2023

It allows engineers to easily create visualization dashboards by collecting data from multiple sources through a user-friendly interface. It aids in tasks like generating real-time dashboards and preparing data reports. Power BI: One of the best tools for data visualization and business intelligence is Microsoft Power BI.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 30, 2024

Extraction: This initial step involves retrieving data from one or multiple sources or systems. During extraction, the process identifies and isolates the relevant data, preparing it for subsequent processing or transformation. Transformation: Once the data has been successfully extracted, it enters the refinement phase.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Edureka

DECEMBER 12, 2023

Innovation,DetailOriented Business Systems Analyst INR 9,78,494 Problem solving , Data analysis , Project Management Reporting Analyst INR 4,00,000 Data and information visualization, Critical thinking, Analytical reasoning.

Business Analyst 40

Business Analyst Consulting NoSQL Manufacturing 40

Knowledge Hut

OCTOBER 27, 2023

Microsoft created Power BI, a business analytics tool that enables users to visualize and analyze data from various sources quickly and interactively. It provides a wide range of features and functionalities, including data preparation, data modeling, data visualization, and collaboration tools.

BI 52

BI Project Datasets Healthcare 52

ProjectPro

OCTOBER 6, 2021

So to fix this problem, one can use smart traffic management, which uses Google’s infrastructure to store data and adhere to quick response time. Source : Storage.googleapis.com This GCP project involves collecting different and real-time traffic data. This data is then analyzed and mined using business intelligence tools.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 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

MAY 20, 2015

Fred Shilmover, CEO of InsightSquared says- "It's an exciting time to be in the big data analytics space pointing to recent developments such as Tableau Software's highly successful IPO and a $125 million funding round for Domo. Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

AltexSoft

OCTOBER 30, 2021

A data scientist takes part in almost all stages of a machine learning project by making important decisions and configuring the model. Data preparation and cleaning. Final analytics are only as good and accurate as the data they use. Data engineer’s responsibilities — Development and Architecture.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Knowledge Hut

APRIL 19, 2023

Talend: A commercial ETL tool that supports batch and real-time data integration.It provides connectors for data sources and symbols, as well as a visual interface for designing ETL pipelines. Informatica PowerCenter: A business ETL tool that supports batch and real-time data integration.

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

Knowledge Hut

DECEMBER 7, 2023

Parameters Power BI DevOps Functionalities Business intelligence. Power BI vs DevOps: Functionalities Power BI functionality: Business intelligence can be performed using Microsoft Power BI, a SAAS-based tool. It transforms data from many sources in order to create dynamic dashboards and Business Intelligence reports.

BI 52

BI Business Intelligence Datasets 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 Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer performs a multi-faceted role in an organization by identifying, extracting, and delivering the data sets in useful formats. For example, Machine Learning is one of the skills excessively in-demand and is essential for a Big Data Engineer. The following table illustrates the key differences between these roles.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 31, 2022

This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse? A Data Warehouse is a central information repository that enables Data Analytics and Business Intelligence (BI) activities. Snowflake allows data to be examined and cleaned immediately, assuring data integrity.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MAY 14, 2021

With the ETL approach, data transformation happens before it gets to a target repository like a data warehouse, whereas ELT makes it possible to transform data after it’s loaded into a target system. Data storage and processing. Also, Spark supports machine learning (MLlib), SQL, graph processing (GraphX). Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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 AWS Relational Database 52

ProjectPro

JUNE 24, 2021

Access Solution to Building IT Job Portal using Twitter Data 20) Implementing Slowly Changing Dimensions in a Data Warehouse: Slowly Changing Dimensions (SCD) are data entities in a data warehouse which remain fairly static over time and change very slowly rather than at regular or frequent time intervals.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

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 Government Data Science 52

The Modern Data Company

JANUARY 22, 2024

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. Data engineering excellence Modern offers robust solutions for building, managing, and operationalizing data pipelines.

Data Integration 98

Data Integration Metadata Government Unstructured Data 98

The Modern Data Company

JANUARY 22, 2024

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. This capability is instrumental in meeting the analytical demands of various data applications, including analytics, business intelligence (ABI), and data science.

Data Integration 87

Data Integration Metadata Government Unstructured Data 87

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. What Databricks is used for Use cases for Databricks are as diverse and numerous as the types of data and the range of tools and operations it supports.

Scala 64

Scala Data Lake BI Google Cloud 64