The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Companies need more than definitions. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Companies need more than definitions. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Companies need more than definitions. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

AltexSoft

JUNE 26, 2023

Data collection as the first step in the decision-making process, driven by machine learning. In machine learning projects, data collection precedes such stages as data cleaning and preprocessing, model training and testing, and making decisions based on a model’s output. Data engineering explained in 14 minutes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Knowledge Hut

APRIL 25, 2024

One of the industries with the quickest growth rates is big data. It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. What Are the Different Features of Big Data Analytics? The main features of big data analytics are: 1.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

AltexSoft

MAY 12, 2023

By understanding these aspects comprehensively, you can harness the true potential of unstructured data and transform it into a strategic asset. What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. This is one of the major reasons behind the popularity of data science. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

FEBRUARY 16, 2023

For example, the data manipulation language (DML) and data definition language (DDL) allow engineers to collect and manipulate data scripts and design and modify data structures. Your SQL skills as a data engineer are crucial for data modeling and analytics tasks.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

U-Next

OCTOBER 20, 2022

By the time you’re finished reading this, you’ll know why choosing the appropriate data collection strategy is essential for attaining your specified goal. . What is Data Collection? A Definition . The data collection methods enable a person to get a conclusion on the relevant subject.

Data Collection 52

Data Collection Big Data Data Medical 52

AltexSoft

MARCH 30, 2023

Shell, Adobe, Burberry, Columbia, Bayer — you definitely know the names. The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions.

Scala 64

Scala Data Lake BI Google Cloud 64

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data is generally not loaded into a data warehouse unless a use case has been defined for the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

AUGUST 31, 2023

A NASA space probe, the Mars Climate Orbiter crashed as a result of a data entry error that produced outputs in non-SI (International System) units versus SI units, bringing it too close to the planet. Like spacecraft, analytic pipelines can be extremely vulnerable to the most innocent changes at any stage of the process.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. How HDFS master-slave structure works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Picnic Engineering

JULY 24, 2023

Introduction Transformer models have revolutionized natural language processing with their human-like text generation capabilities. By converting raw data into valuable information, transformer models could significantly contribute to sustainability. Notably, approximately 20% of the dataset is allocated for evaluation.

Datasets 52

Datasets Architecture Utilities Raw Data 52

Rockset

JANUARY 28, 2020

Adding external data sources, each with a different schema, can require significant effort building and maintaining ETL pipelines. Testing new functionality on their transactional data store is costly and can impact production. When in the experimental phase, quick schema changes are required when analyzing their data.

Retail 40

Retail Google Cloud Raw Data Data Lake 40

ProjectPro

MAY 31, 2021

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. Access Solution to Data Warehouse Design for an E-com Site 4.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

OCTOBER 18, 2021

To build such ML projects, you must know different approaches to cleaning raw data. Statistical modeling: Here, the student has to prepare a real-world model of the mathematical representation and the statistics uncertainties within the analyzing and prediction process. Text Processing b. Text Sequencing c.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

APRIL 27, 2016

With the need to simplify big data technologies, various open source innovations have been developed on top of Hadoop to handle mission critical workloads. A lot of innovations have been tagged along the tiny toy elephant, which work together if an organization knows how to make these big data tools work.

Hadoop 40

Hadoop Big Data Technology Big Data Tools 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.

Hadoop 40

Hadoop Big Data Metadata Java 40