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 Engineer 98

Data Engineer Data Engineering Engineering Unstructured Data 98

Monte Carlo

OCTOBER 31, 2024

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Let’s dive into the tools necessary to become an AI data engineer. Let’s examine a few.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Monte Carlo

FEBRUARY 12, 2024

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories. Quality : Is the data itself anomalous?

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Data Engineering Weekly

JUNE 24, 2024

A few highlights from the report Unstructured data goes mainstream. Question to the readers, what do you think of the current state of real-time data processing engines? link] Influx Data: How Good is Parquet for Wide Tables (Machine Learning Workloads) Really? AI-driven code development is going mainstream now.

Data Engineer 109

Data Engineer Data Engineering Engineering Google Cloud 109

Monte Carlo

OCTOBER 10, 2024

Let’s dive into the responsibilities, skills, challenges, and potential career paths for an AI Data Quality Analyst today. Table of Contents What Does an AI Data Quality Analyst Do? Handling unstructured data Many AI models are fed large amounts of unstructured data, making data quality management complex.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 52

AltexSoft

DECEMBER 23, 2022

Integrating data from numerous, disjointed sources and processing it to provide context provides both opportunities and challenges. One of the ways to overcome challenges and gain more opportunities in terms of data integration is to build an ELT (Extract, Load, Transform) pipeline. Order of process phases. What is ELT?

Process 52

Process Building Raw Data Data Lake 52

Striim

OCTOBER 11, 2024

Then, we’ll explore a data pipeline example and dive deeper into the key differences between a traditional data pipeline vs ETL. What is a Data Pipeline? A data pipeline refers to a series of processes that transport data from one or more sources to a destination, such as a data warehouse, database, or application.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

phData: Data Engineering

NOVEMBER 8, 2024

Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms. These systems are built on open standards and offer immense analytical and transactional processing flexibility. Why should we use it?

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. Marini et al This results in a very large amount of data for a single slide, often a few gigabytes per slide, which is all stored in one big file. data import torch. import pandas as pd import PIL.

Medical 60

Medical Process Cloud Bytes 60

Knowledge Hut

AUGUST 16, 2024

Academic Prerequisites To become a successful Data Scientist, you need an undergraduate or a postgraduate degree in Computer Science, Mathematics, Statistics, Business Information Systems, Information Management , or any other similar field. It also helps in saving time by distributing data processing when the dataset size is large.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

Knowledge Hut

APRIL 25, 2024

Big data vs machine learning is indispensable, and it is crucial to effectively discern their dissimilarities to harness their potential. Big Data vs Machine Learning Big data and machine learning serve distinct purposes in the realm of data analysis.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Snowflake

APRIL 10, 2023

Discover how Snowflake’s Data Cloud is helping semantic processing platform, semantha, reach its full potential—with Accenture’s support. semantha is a semantic processing platform that understands and processes human language—at astonishing scale and speed. From there, we can process information not unlike how humans do.

Unstructured Data 59

Unstructured Data Manufacturing Insurance Government 59

Knowledge Hut

APRIL 23, 2024

They also facilitate historical analysis, as they store long-term data records that can be used for trend analysis, forecasting, and decision-making. Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Data Engineering Weekly

SEPTEMBER 18, 2024

The Rise of Data Observability Data observability has become increasingly critical as companies seek greater visibility into their data processes. This growing demand has found a natural synergy with the rise of the data lake. What is the Difference Between Data Testing and Data Observability?

Data Lake 98

Data Lake Data Pipeline Unstructured Data Datasets 98

Snowflake

APRIL 8, 2024

BigGeo BigGeo accelerates geospatial data processing by optimizing performance and eliminating challenges typically associated with big data. The Innova-Q dashboard provides access to product safety and quality performance data, historical risk data, and analysis results for proactive risk management.

Pipeline-centric 128

Pipeline-centric Food Healthcare Unstructured Data 128

Knowledge Hut

MAY 3, 2024

Cluster Computing: Efficient processing of data on Set of computers (Refer commodity hardware here) or distributed systems. It’s also called a Parallel Data processing Engine in a few definitions. Spark is utilized for Big data analytics and related processing. Why Apache Spark? Let’s discuss one by one.

Scala 98

Scala Hadoop Healthcare Big Data 98

Striim

SEPTEMBER 11, 2024

With data volumes and sources rapidly increasing, optimizing how you collect, transform, and extract data is more crucial to stay competitive. That’s where real-time data, and stream processing can help. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

DECEMBER 21, 2023

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. To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Precisely

APRIL 30, 2024

RPA is best suited for simple tasks involving consistent data. It’s challenged by complex data processes and dynamic environments Complete automation platforms are the best solutions for complex data processes. Integration issues: Complex processes often involve interacting with multiple systems and applications.

Unstructured Data 59

Unstructured Data Government Data Validation Programming 59

Data Engineering Weekly

DECEMBER 25, 2023

The Rising Impact of AI and Large Language Models 2023 witnessed a substantial impact of AI and large language models in data engineering. These technologies are increasingly automating processes like ETL, improving data quality management, and evolving the landscape of data tools.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Snowflake

JANUARY 18, 2024

A robust, flexible architecture Snowflake’s unique architecture is designed to handle the full volume, velocity and variety of data without making manufacturers deal with downtime for upgrades or compute changes. In addition, Snowflake is cloud-agnostic and can be moved to and from different cloud environments.

Manufacturing 89

Manufacturing Unstructured Data Cloud Architecture 89

Knowledge Hut

MAY 23, 2024

It helps companies understand data and obtain meaningful insights from it. According to the GlobeNewswire report , the projected growth of the data science market will hike up to a CAGR of 25 percent by 2030. With the increase in the demand for data science, job opportunities are also exponentially high.

Data Science 52

Data Science MongoDB Programming Language Hadoop 52

Knowledge Hut

APRIL 23, 2024

Results Broader and exploratory results Targeted results Big Data vs Data Mining Here is a more detailed illustration of the difference between big data and data mining:- 1. Traditional data processing techniques cannot be used. Data mining is capable of handling comparatively smaller datasets.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Monte Carlo

AUGUST 25, 2023

So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform? Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Let’s dive in. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Snowflake

NOVEMBER 29, 2023

For example, the data storage systems and processing pipelines that capture information from genomic sequencing instruments are very different from those that capture the clinical characteristics of a patient from a site. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 87

Metadata Healthcare Medical Data Storage 87

DoorDash Engineering

APRIL 26, 2023

The company is exploring the use of Generative AI, a subset of Artificial Intelligence that generates novel content based on existing data, and how it can be implemented effectively with consideration for the privacy and security of personal information. These suggestions save time for customers and can simplify the ordering process.

Food 98

Food Unstructured Data Deep Learning SQL 98

Cloudera

FEBRUARY 15, 2024

Scalability and future-proofing: Modern data architecture offers robust data integration capabilities, allowing efficient and real-time data ingestion from various sources, including structured databases, unstructured data, streaming data, and external data feeds.

Insurance 88

Insurance Banking Data Architecture Data Ingestion 88

Striim

AUGUST 28, 2024

These roles will span various sectors, including data science, AI ethics, machine learning engineering, and AI-related research and development. Real-Time Data — The Missing Link What is Real-Time Data? Batch processing resulted in significant delays between data generation and actionable insights.

Healthcare 52

Healthcare Retail Algorithm Finance 52

Knowledge Hut

DECEMBER 26, 2023

Importance of Big Data Companies Big Data is intricate and can be challenging to access and manage because data often arrives quickly in ever-increasing amounts. Both structured and unstructured data may be present in this data. Thus, big data in big companies is used for various purposes.

Big Data 52

Big Data Unstructured Data Amazon Web Services Hadoop 52

Knowledge Hut

APRIL 23, 2024

These data sets consist of extensive and intricate data from diverse sources, including business transactions, social media interactions, and sensor data. Big data stands out due to its significant volume, quick velocity, and wide variety, leading to difficulties in storage, processing, analysis, and interpretation.

Big Data 52

Big Data Media Datasets Unstructured Data 52

U-Next

MARCH 1, 2023

Being a hybrid role, Data Engineer requires technical as well as business skills. They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. What is AWS Kinesis?

Data Engineer 75

Data Engineer Data Engineering Non-relational Database Engineering 75

Striim

AUGUST 31, 2023

Showing how Kappa unifies batch and streaming pipelines The development of Kappa architecture has revolutionized data processing by allowing users to quickly and cost-effectively reduce data integration costs. Stream processors, storage layers, message brokers, and databases make up the basic components of this architecture.

Data Integration 69

Data Integration Architecture Amazon Web Services Machine Learning 69

Knowledge Hut

APRIL 23, 2024

As big data evolves and unravels more technology secrets, it might help users achieve ambitious targets. But do you know there are certain disadvantages of big data along with the pros? This article will talk about the challenges faced in using, storing, processing, and retrieving big data.

Big Data 52

Big Data Media Government Big Data Skills 52

Monte Carlo

MAY 28, 2024

This involves connecting to multiple data sources, using extract, transform, load ( ETL ) processes to standardize the data, and using orchestration tools to manage the flow of data so that it’s continuously and reliably imported – and readily available for analysis and decision-making.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 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 Data Lake Management 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