ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Hepta Analytics

FEBRUARY 14, 2022

When the business intelligence needs change, they can go query the raw data again. ELT: source Data Lake vs Data Warehouse Data lake stores raw data. The purpose of the data is not determined. The data is easily accessible and is easy to update.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Rockset

AUGUST 2, 2023

The Windward Maritime AI platform Lastly, Windward wanted to move their entire platform from batch-based data infrastructure to streaming. This transition can support new use cases that require a faster way to analyze events that was not needed until now. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Knowledge Hut

JANUARY 18, 2024

Let us now look into the differences between AI and Data Science: Data Science vs Artificial Intelligence [Comparison Table] SI Parameters Data Science Artificial Intelligence 1 Basics Involves processes such as data ingestion, analysis, visualization, and communication of insights derived.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Knowledge Hut

JANUARY 18, 2024

However, while anyone may access raw data, you can extract relevant and reliable information from the numbers that will determine whether or not you can achieve a competitive edge for your company. When people speak about insights in data science, they generally mean one of three components: What is Data?

Data Science 52

Data Science Media Food Data 52

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 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. Major Big Data analytics tools and services.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Rockset

JANUARY 28, 2020

Schemaless Ingest for Running Experiments Standard builds their production systems to access the streams of events they collect through a number of backend APIs, and the team is continually adding new API endpoints to make more data available to developers. How accurate were the AI models compared to human-resolved events?

Retail 40

Retail Google Cloud Raw Data Data Lake 40

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Picnic Engineering

JULY 24, 2023

Challenges in Traditional Demand Forecasting Traditional ways of predicting product demand are based on past sales data, seasonal patterns, events, and broad product categories. By converting raw data into valuable information, transformer models could significantly contribute to sustainability.

Datasets 52

Datasets Architecture Utilities Raw Data 52

AltexSoft

SEPTEMBER 23, 2021

The result of experimentation supplies downstream applications with prepared data. A data hub serves as a gateway to dispense the required data. So the use of unstructured or semi-structured data is also available in a data hub, since a data lake can be a part of it. Cumulocity IoT data hub platform.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Monte Carlo

JUNE 14, 2023

Airbyte – An open source platform that easily allows you to sync data from applications. Data streaming ingestion solutions include: Apache Kafka – Confluent is the vendor that supports Kafka, the open source event streaming platform to handle streaming analytics and data ingestion.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 18, 2021

By the end of 2022, the industry will experience a huge demand for data analysts, data scientists, and BI professionals with decent Tableau knowledge. . · · Tableau also provides a data blending facility. Which Tableau data types are preferable while dealing with structured data?

BI 40

BI Database-centric SQL Software Engineer 40

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. They just need to deliver their data and hand it over to Snowflake to manage.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

MARCH 14, 2014

Online FM Music 100 nodes, 8 TB storage Calculation of charts and data testing 16 IMVU Social Games Clusters up to 4 m1.large Online FM Music 100 nodes, 8 TB storage Calculation of charts and data testing 16 IMVU Social Games Clusters up to 4 m1.large Hadoop is used at eBay for Search Optimization and Research.

Hadoop 40

Hadoop Big Data Data Mining Retail 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

NOVEMBER 14, 2015

Big data technologies used: Microsoft Azure, Azure Data Factory, Azure Databricks, Spark Big Data Architecture: This sample Hadoop real-time project starts off by creating a resource group in azure. To this group, we add a storage account and move the raw data.

Hadoop 52

Hadoop Project Big Data Healthcare 52