Edureka

MAY 8, 2025

These are the ways that data engineering improves our lives in the real world. The field of data engineering turns unstructured data into ideas that can be used to change businesses and our lives. Data engineering can be used in any way we can think of in the real world because we live in a data-driven age.

Data Engineering 52

Data Engineering Data Engineer Engineering Telecommunication 52

Rockset

NOVEMBER 1, 2018

Over a decade after the inception of the Hadoop project, the amount of unstructured data available to modern applications continues to increase. This longevity is a testament to the community of analysts and data practitioners who are familiar with SQL as well as the mature ecosystem of tools around the language.

Raw Data 40

Raw Data SQL Unstructured Data NoSQL 40

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.

Engineering 102

Engineering Raw Data Data Science Machine Learning 102

Knowledge Hut

JANUARY 18, 2024

Speaking of job vacancies, the two careers have high demands till date and in upcoming years are Data Scientist and a Software Engineer. Per the BLS, the expected growth rate of job vacancies for data scientists and software engineers is around 22% by 2030. What is Data Science? Get to know more about SQL for data science.

Software Engineer 97

Software Engineer Software Engineering Data Science Engineering 97

Towards Data Science

MAY 3, 2023

Data Engineering Learn about slow change dimensions (SCD) and how to implement SCD Type 2 in VDK Photo by Joshua Sortino on Unsplash Data is the backbone of any organization, and in today’s fast-paced world, it is crucial to keep track of its versions. They store and manage current and historical data in a data warehouse.

Data Lake 98

Data Lake Data SQL Data Warehouse 98

Snowflake

JUNE 30, 2023

To make that happen, it leverages the breadth of the Snowflake platform to transform raw data from multiple financial and operational systems into a common data model that users can understand more easily. semantha seeks to eliminate information overload with AI services for processing unstructured data like text and video.

Unstructured Data 98

Unstructured Data Raw Data Python SQL 98

Knowledge Hut

JANUARY 18, 2024

Data Science has risen to become one of the world's topmost emerging multidisciplinary approaches in technology. Recruiters are hunting for people with data science knowledge and skills these days. Data Scientists collect, analyze, and interpret large amounts of data. Choose data sets.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

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. What is Data Science? What are the roles and responsibilities of a Data Engineer? What is the need for Data Science?

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lake 58

Data Lake Data Warehouse Hadoop Raw Data 58

Knowledge Hut

DECEMBER 22, 2023

Data analytics, data mining, artificial intelligence, machine learning, deep learning, and other related matters are all included under the collective term "data science" When it comes to data science, it is one of the industries with the fastest growth in terms of income potential and career opportunities.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Towards Data Science

FEBRUARY 9, 2024

How to build a modern, scalable data platform to power your analytics and data science projects (updated) Table of Contents: What’s changed? The Platform Integration Data Store Transformation Orchestration Presentation Transportation Observability Closing What’s changed? Over the last three years, my life has changed as well.

Building 98

Building Transportation Data Lake Metadata 98

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Most importantly, these pipelines enable your team to transform data into actionable insights, demonstrating tangible business value.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

AUGUST 25, 2023

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

SEPTEMBER 15, 2022

Cloudera Contributor: Mark Ramsey, PhD ~ Globally Recognized Chief Data Officer. July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. Luke: What is a modern data platform?

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Data Engineering Weekly

MAY 8, 2023

Your colleague, Helen from finance, optimistically informs you that this should be easy since all the data has been entered into the company's databases. Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone.

Process 52

Process Banking Raw Data Finance 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? . What is Data Lake? .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Monte Carlo

FEBRUARY 25, 2025

Data pipelines are messy. Data engineering design patterns are repeatable solutions that help you structure, optimize, and scale data processing, storage, and movement. They make data workflows more resilient and easier to manage when things inevitably go sideways. Data lake or warehouse? Lets take a look.

Designing 52

Designing Data Engineering Data Engineer Engineering 52

Monte Carlo

MARCH 12, 2025

Data lakes turned into swamps , pipelines burst, and just when you thought youd earned a degree in hydrology, someone leaned in and whispered: Delta Lake. Are we building data dams next? Lets break it down and see when a plain data lake works and when youll want the extra reliability of Delta Lake. What is a data lake used for?

Data Lake 52

Data Lake Raw Data Media Unstructured Data 52

Sync Computing

NOVEMBER 7, 2024

Data is central to modern business and society. Depending on what sort of leaky analogy you prefer, data can be the new oil , gold , or even electricity. Of course, even the biggest data sets are worthless, and might even be a liability, if they arent organized properly.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

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

Knowledge Hut

AUGUST 16, 2024

Data Science is one of the fastest-growing, trending tech career tracks. But with so many options around, it can be over whelming to take the perfect first step into the field of data science. In this article, we will look at all the technical and non-technical prerequisites to kickstart a career in Data Science.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

Knowledge Hut

APRIL 26, 2024

Also called data storage areas , they help users to understand the essential insights about the information they represent. Machine Learning without data sets will not exist because ML depends on data sets to bring out relevant insights and solve real-world problems. In the real world, data sets are huge.

Machine Learning 98

Machine Learning Datasets Deep Learning Finance 98

Meltano

OCTOBER 5, 2022

Interested in becoming a data engineer? The need for data experts in the U.S. job market is expected to grow by 22% in this decade, and according to LinkedIn’s 2020 report , a data engineer is listed as the 8th fastest growing job today. But what is data engineering exactly and what does a data engineer do?

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

Knowledge Hut

APRIL 23, 2024

Data Science and Business intelligence are popular terms in every business domain these days. Though both have data as the fundamental aspect, their uses, and operations vary. Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. What Does a Data Processing Analyst Do?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

AltexSoft

MAY 12, 2022

Particularly, we’ll explain how to obtain audio data, prepare it for analysis, and choose the right ML model to achieve the highest prediction accuracy. But first, let’s go over the basics: What is the audio analysis, and what makes audio data so challenging to deal with. What is audio data? Audio data file formats.

Machine Learning 122

Machine Learning Building Deep Learning Healthcare 122

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Grouparoo

NOVEMBER 16, 2021

For organizations that manage large volumes of data, leveraging maximum value from the information buried in the data can be a challenge. Breaking silos and collating data into a coherent set of information for processing will yield business benefits. This is where data transformation can come to the rescue.

Data Mining 52

Data Mining Raw Data ETL Tools Data 52

AltexSoft

JUNE 26, 2023

All successful companies do it: constantly collect data. While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Ascend.io

DECEMBER 14, 2022

As data became the backbone of most businesses, data integration emerged as one of the most significant challenges. Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

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. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

AltexSoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78