Data Engineering Weekly

MARCH 5, 2025

In the mid-2000s, Hadoop emerged as a groundbreaking solution for processing massive datasets. It promised to address key pain points: Scaling: Handling ever-increasing data volumes. Speed: Accelerating data insights. Like Hadoop, it aims to tackle scalability, cost, speed, and data silos.

Hadoop 57

Hadoop Metadata Data Ingestion Data Governance 57

Monte Carlo

JULY 15, 2024

We recently spoke with Killian Farrell , Principal Data Scientist at insurance startup AssuranceIQ to learn how his team built an LLM-based product to structure unstructured data and score customer conversations for developing sales and customer support teams. Read on to find out what they did, and what they learned!

Unstructured Data 94

Unstructured Data Insurance Data Lake Structured Data 94

Data Engineering Weekly

JULY 14, 2024

[link] Sponsored: 7/25 Amazon Bedrock Data Integration Tech Talk Streamline & scale data integration to and from Amazon Bedrock for generative AI applications. Senior Solutions Architect at AWS) Learn about: Efficient methods to feed unstructured data into Amazon Bedrock without intermediary services like S3.

Data Engineering 98

Data Engineering Data Engineer Engineering Unstructured Data 98

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies. Increased confidence in data results in trusted AI.

Cloud 105

Cloud Unstructured Data Metadata Government 105

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

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

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

We also integrate GenAI into the Monte Carlo product itself to make the lives of data teams easier through AI-powered monitor recommendations , fixes with AI, and soon, Gen-AI powered root cause analysis (stay tuned for more on that soon). 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

We also integrate GenAI into the Monte Carlo product itself to make the lives of data teams easier through AI-powered monitor recommendations , fixes with AI, and soon, Gen-AI powered root cause analysis (stay tuned for more on that soon). This workflow creates a good balance between speed, cost, and quality of results.

AWS 52

AWS Google Cloud Unstructured Data Coding 52

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

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

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

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

Data Engineering Weekly

APRIL 7, 2024

[link] Matt Turck: Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape Coninue the week of insights into the world of data & AI landscape, the 2024 MAD landscape is out. We index only top-tier tables, promoting the use of these higher-quality datasets.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

Monte Carlo

OCTOBER 10, 2024

Table of Contents What Does an AI Data Quality Analyst Do? Essential Skills for an AI Data Quality Analyst There are several important skills an AI Data Quality Analyst needs to know in order to successfully ensure and maintain accurate, reliable AI models. Machine Learning Basics : Understanding how data impacts model training.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 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

AUGUST 16, 2024

Mathematics / Stastistical Skills While it is possible to become a Data Scientist without a degree, it is necessary to have Mathematical skills to become a Data Scientist. Let us look at some of the areas in Mathematics that are the prerequisites to becoming a Data Scientist.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

RandomTrees

MAY 6, 2025

However, to succeed, AI requires a foundation of reliable and structured data. Modern data engineering can help with this. It creates the systems and processes needed to gather, clean, transfer, and prepare data for AI models. Without it, AI technologies wouldn’t have access to high-quality data.

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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

DECEMBER 26, 2023

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

JULY 28, 2023

Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. DL models excel at handling unstructured data such as images, audio, and text, where the data has a large number of features or high dimensionality.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

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

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

OCTOBER 25, 2021

This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. Some of it is structured , or organized into specific fields of an EHR. Unstructured data is unavoidable, yet extremely valuable. The many healthcare factors hidden in unstructured data.

Medical 52

Medical Healthcare Process Hospitality 52

Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Monte Carlo

FEBRUARY 15, 2023

Data can be loaded using a loading wizard, cloud storage like S3, programmatically via REST API, third-party integrators like Hevo, Fivetran, etc. Data can be loaded in batches or can be streamed in near real-time. Structured, semi-structured, and unstructured data can be loaded.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Specification of access conditions for specific users and groups.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

ProjectPro

OCTOBER 15, 2014

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. We generally refer to Unstructured Data as “Big Data” and the framework that is used for processing Big Data is popularly known as Hadoop.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you. js: To create interactive and customizable charts, D3.js

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

ProjectPro

SEPTEMBER 9, 2021

The datasets are usually present in Hadoop Distributed File Systems and other databases integrated with the platform. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data. Apache Spark , on the other hand, is an analytics framework to process high-volume datasets.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Rockset

JULY 29, 2022

This fast, serverless, highly scalable, and cost-effective multi-cloud data warehouse has built-in machine learning, business intelligence, and geospatial analysis capabilities for querying massive amounts of structured and semi-structured data. BigQuery aims to provide fast queries on massive datasets.

Data Analytics 52

Data Analytics Data Warehouse Datasets Cloud 52

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Edureka

FEBRUARY 12, 2025

Integration with External Data : LangChain lets LLMs talk to APIs, databases, and other data sources. This lets them do things like get real-time information or process datasets that are specific to a topic. Databases Facilitates storage and retrieval of structured data. Some important reasons are: 1.

IT 52

IT Database Google Cloud Coding 52

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52