ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Explain the data preparation process. Steps for Data preparation.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

DECEMBER 7, 2023

Within Power BI, you may convert, model, and clean the data to produce a unified, organized dataset that accurately represents the data you wish to examine. Dataflows: Before raw data is entered into datasets, several data transformation stages can be conducted using dataflows.

BI 52

BI Raw Data Datasets Business Intelligence 52

Monte Carlo

MAY 25, 2023

Some of the value companies can generate from data orchestration tools include: Faster time-to-insights. Automated data orchestration removes data bottlenecks by eliminating the need for manual data preparation, enabling analysts to both extract and activate data in real-time. Improved data governance.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Edureka

FEBRUARY 7, 2023

To prepare for the exam, you should have hands-on experience using Azure data services to design and build data engineering solutions. It covers topics such as data ingestion, data transformation, and data delivery, as well as data storage, data processing, and data security.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

Rockset

AUGUST 30, 2021

It eliminates the cost and complexity around data preparation, performance tuning and operations, helping to accelerate the movement from batch to real-time analytics. The latest Rockset release, SQL-based rollups, has made real-time analytics on streaming data a lot more affordable and accessible.

SQL 52

SQL Kafka MongoDB MySQL 52

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

ProjectPro

DECEMBER 6, 2016

Pentaho published a whitepaper titled “Hadoop and the Analytic Data Pipeline” that highlights the key categories which need to be focused on - Big Data Ingestion, Transformation, Analytics, Solutions. Source: [link] ) How Trifacta is helping data wranglers in Hadoop, the cloud, and beyond.Zdnet.com, November 4,2016.

Hadoop 52

Hadoop Data Lake BI Big Data 52

Rockset

OCTOBER 4, 2022

Data Ingestion Streaming vs Batch Ingestion While ClickHouse offers several ways to integrate with Kafka to ingest event streams, including a native connector, ClickHouse ingests data in batches. In contrast, there is no recommendation to denormalize data in Rockset, as Rockset can handle JOINs well.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

ProjectPro

FEBRUARY 8, 2023

It allows you to create Apache Spark workflows for data ingestion and transformation that read from and write to data in Amazon Redshift. These workflows maintain performance and transactional data consistency with the new connector and driver.

AWS 98

AWS Scala Metadata Data Lake 98

Zalando Engineering

MARCH 21, 2017

Moving deep-learning machinery into production requires regular data-aggregation-, model-training- and prediction-tasks. Data Preparation Before any machine learning is applied, data has to be gathered and organized to fit the input format of the machine learning model.

Deep Learning 52

Deep Learning Raw Data Machine Learning AWS 52

ProjectPro

NOVEMBER 15, 2021

In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks. Apache Zeppelin Source: Github Apache Zeppelin is a multi-purpose notebook that supports Data Ingestion, Data Discovery, Data Analytics , Data Visualization , and Data Collaboration.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

MAY 31, 2021

There are open data platforms in several regions (like data.gov in the U.S.). These open data sets are a fantastic resource if you're working on a personal project for fun. Data Preparation and Cleaning The data preparation step, which may consume up to 80% of the time allocated to any big data or data engineering project, comes next.

Big Data 52

Big Data Coding Project Hadoop 52

Cloudera

MARCH 31, 2021

One of our customers, Commerzbank, has used the CDP Public Cloud trial to prove that they can combine both Google Cloud and CDP to accelerate their migration to Google Cloud without compromising data security or governance. . Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 91

Google Cloud Cloud Amazon Web Services Cloud Storage 91

Cloudera

JUNE 4, 2018

Aspire , built by Search Technologies , part of Accenture is a search engine independent content processing framework for handling unstructured data. It provides a powerful solution for data preparation and publishing human-generated content to search engines and big data applications.

Pharmaceutical 45

Pharmaceutical Unstructured Data Electronics Metadata 45

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

U-Next

JUNE 29, 2022

Preparing data for analysis is known as extract, transform and load (ETL). While the ETL workflow is becoming obsolete, it still serves as a common word for the data preparation layers in a big data ecosystem. Working with large amounts of data necessitates more preparation than working with less data.

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Let’s take a closer look at these procedures. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 91

Data Engineering Data Engineer Cloud Engineering 91

U-Next

SEPTEMBER 23, 2022

In Big Data systems, data can be left in its raw form and subsequently filtered and structured as needed for specific analytical needs. In other circumstances, it is preprocessed using data mining methods and data preparation software to prepare it for ordinary applications. .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

AltexSoft

JULY 8, 2021

Adaptive , meaning models should have a proper data pipeline for regular data ingestion, validation, and deployment to timely adjust to changes. The typical machine learning scenario data scientists leverage to bring propensity modeling to life involves the following steps: Mapping out a strategy. Deploying a model.

Machine Learning 78

Machine Learning Algorithm Education Data Science 78

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. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake BI Google Cloud 64