Data Engineering Podcast

FEBRUARY 3, 2019

Open Context is an open access data publishing service for archaeology. It started because we need better ways of dissminating structured data and digital media than is possible with conventional articles, books and reports. What are your protocols for determining which data sets you will work with?

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

Knowledge Hut

FEBRUARY 29, 2024

Then, based on this information from the sample, defect or abnormality the rate for whole dataset is considered. This process of inferring the information from sample data is known as ‘inferential statistics.’ A database is a structured data collection that is stored and accessed electronically.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

Knowledge Hut

MAY 3, 2024

Types of Machine Learning: Machine Learning can broadly be classified into three types: Supervised Learning: If the available dataset has predefined features and labels, on which the machine learning models are trained, then the type of learning is known as Supervised Machine Learning. Example: Let us look at the structure of a decision tree.

Machine Learning 98

Machine Learning Algorithm Datasets Medical 98

Knowledge Hut

MAY 2, 2024

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. collect(): Return all the elements of the dataset as an array at the driver program.

Hadoop 96

Hadoop Scala Datasets Java 96

Data Engineering Weekly

FEBRUARY 9, 2025

MoEs necessitate less compute for pre-training compared to dense models, facilitating the scaling of model and dataset size within similar computational budgets. Try Astro Free → Hugging Face: Mixture of Experts Explained The mixture of Experts (MoEs) are transformer models efficiently gaining traction in the open AI community.

Data Engineering 58

Data Engineering Data Engineer Engineering Unstructured Data 58

Monte Carlo

JULY 15, 2024

Not only can the LLM turn unstructured data into structured data, but it can also give a summary of exactly what happened – and it can do so dynamically, so new context is always added and taken into account. This new dataset opened the door for even more machine learning analysis on newly structured data.

Unstructured Data 94

Unstructured Data Insurance Data Lake Structured Data 94

Netflix Tech

OCTOBER 27, 2020

The field names should exactly match for Bulldozer to convert the structured data entries into the key-value pairs. Users can use the protobuf schema KeyMessage and ValueMessage to deserialize data from Key-Value DAL as well. Each execution moves the latest view of the data warehouse into a Key-Value DAL namespace.

Data Warehouse 100

Data Warehouse Datasets Data Big Data 100

Knowledge Hut

MAY 31, 2023

Resume Parser Language: Python Data set: text file Source code: keras-english-resume-parser-and-analyzer An AI-powered tool called a resume parser pulls pertinent data from resumes or CVs and turns it into structured data. Take online classes: Work with real-world datasets to put your knowledge into practice.

Project 96

Project Healthcare Deep Learning Transportation 96

Edureka

FEBRUARY 13, 2025

Moreover, these models struggle with domain shift, where the statistical distribution of training data varies from that of new data (e.g., Training the Similarity Function A big-named dataset like ImageNet is used to teach the model how to understand similarities in a supervised way.

Deep Learning 52

Deep Learning Datasets Data Machine Learning 52

AltexSoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. A powerful Big Data tool, Apache Hadoop alone is far from being almighty.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. Increased confidence in data results in trusted AI. Unlike software, ML models need continuous tuning.

Cloud 105

Cloud Unstructured Data Metadata Government 105

Cloudera

NOVEMBER 15, 2021

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. Data scrutiny. Data fairness is one of the dimensions of ethical AI.

Unstructured Data 90

Unstructured Data Pipeline-centric Database-centric Entertainment 90

Netflix Tech

JULY 21, 2022

This is done by first elaborating on the dataset curation stage?—?specially Since memory management is not something one usually associates with classification problems, this blog focuses on formulating the problem as an ML problem and the data engineering that goes along with it. The dataset will thus be very biased/skewed.

Machine Learning 75

Machine Learning Datasets Big Data Data Pipeline 75

Edureka

APRIL 14, 2025

Interactive exploration : Users can build dashboards that support real-time interaction and deep data exploration. AI-enhanced analytics : Built-in machine learning capabilities help uncover hidden patterns and trends within datasets. Next, we’ll examine the key distinctions between Power BI and Microsoft Fabric.

BI 40

BI Business Intelligence Raw Data Retail 40

Data Engineering Weekly

JULY 14, 2024

(Senior Solutions Architect at AWS) Learn about: Efficient methods to feed unstructured data into Amazon Bedrock without intermediary services like S3. Techniques for turning text data and documents into vector embeddings and structured data. link] All rights reserved ProtoGrowth Inc, India.

Data Engineering 98

Data Engineering Data Engineer Engineering Unstructured Data 98

Knowledge Hut

APRIL 23, 2024

Big data and data mining are neighboring fields of study that analyze data and obtain actionable insights from expansive information sources. Big data encompasses a lot of unstructured and structured data originating from diverse sources such as social media and online transactions.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Edureka

JUNE 7, 2024

paintings, songs, code) Historical data relevant to the prediction task (e.g., Generative AI leverages the power of deep learning to build complex statistical models that process and mimic the structures present in different types of data.

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Precisely

SEPTEMBER 9, 2024

TDWI’s 2024 Data Quality Maturity Model What do organizations at the “Established” level look like? Organizations are adept at managing the quality of structured data, but management of unstructured and semi-structured data is less mature. • Invest in training and culture.

Management 64

Management High Quality Data Structured Data Data Lake 64

Striim

SEPTEMBER 11, 2024

In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset. The dataset can be either structured or unstructured or both. In this article, we will look at some of the top Data Science job roles that are in demand in 2024.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques.

Big Data 52

Big Data Datasets Data Analysis Media 52

Cloudera

JUNE 3, 2022

Data scientists are likely to use a variety of different tools to move through their processes. It could be a homespun version of PostgreSQL on their local machine for exploring structured data sets; to visualize, they could be writing code or using a BI tool like Tableau or PowerBI.

Data Analysis 92

Data Analysis PostgreSQL Data Science Machine Learning 92

Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. link] Daniel Beach: Delta Lake - Map and Array data types Having a well-structured data model is always great, but we often handle semi-structured data.

Data Engineering 68

Data Engineering Data Engineer Engineering Google Cloud 68

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes.

Systems 80

Systems Building Management Data Lake 80

Cloudera

DECEMBER 11, 2020

It established a data governance framework within its enterprise data lake. Powered and supported by Cloudera, this framework brings together disparate data sources, combining internal data with public data, and structured data with unstructured data.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Monte Carlo

MARCH 12, 2025

Lesson 5: Splitting tasks horizontally reduces runtime Lets say we have two tasks we want to perform (pink and blue) on a large dataset. With that expansion comes new challenges and new learning opportunities when it comes to GenAI development. This workflow creates a good balance between speed, cost, and quality of results.

AWS 52

AWS Google Cloud Unstructured Data Coding 52

Monte Carlo

MARCH 12, 2025

Lesson 5: Splitting tasks horizontally reduces runtime Lets say we have two tasks we want to perform (pink and blue) on a large dataset. With that expansion comes new challenges and new learning opportunities when it comes to GenAI development. This workflow creates a good balance between speed, cost, and quality of results.

AWS 52

AWS Google Cloud Unstructured Data Coding 52

Cloudera

SEPTEMBER 26, 2024

However, in order for them to truly excel at specific tasks, like code generation or language translation for rare dialects, they need to be tuned for the task with a more focused and specialized dataset.

Generalist 77

Generalist Machine Learning Datasets Structured Data 77

Monte Carlo

JUNE 6, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Having the data engineering team lead the response to data quality is by far the most common pattern. It is deployed by about half of all organizations that use a modern data stack.

Data Governance 98

Data Governance Government Data Data Engineering 98

Towards Data Science

JUNE 8, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Photo by Luke Chesser on Unsplash Having the data engineering team lead the response to data quality is by far the most common pattern.

Data Governance 98

Data Governance Government Generalist Data Engineering 98

Data Engineering Weekly

APRIL 7, 2024

We index only top-tier tables, promoting the use of these higher-quality datasets. I strongly believe the concept of Data Product will play a bigger role in data engineering. Spotify shares some of the critical triggers in an organization that leads to build data platform.

Data Engineering 71

Data Engineering Data Engineer Engineering Unstructured Data 71

Knowledge Hut

JUNE 28, 2023

Parameter Data Mining Business Intelligence (BI) Definition The process of uncovering patterns, relationships, and insights from extensive datasets. Process of analyzing, collecting, and presenting data to support decision-making. Focus Exploration and discovery of hidden patterns and trends in data.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Precisely

OCTOBER 5, 2023

Determine what data you’ll need Once you’ve determined the use case, brainstorm and dig deeper into what your end goals are and what you need to know to get there. For example, will you need structured data, unstructured, or a combination? sample datasets: are data samples available for download and evaluation?

Raw Data 69

Raw Data Insurance Datasets Telecommunication 69

Knowledge Hut

APRIL 23, 2024

Data storing and processing is nothing new; organizations have been doing it for a few decades to reap valuable insights. Compared to that, Big Data is a much more recently derived term. So, what exactly is the difference between Traditional Data and Big Data? This is a good approach as it allows less space for error.

Big Data 52

Big Data Relational Database Data Structured Data 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. What is Big Data analytics?

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52