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

FEBRUARY 12, 2024

Today, this first-party data mostly lives in two types of data repositories. If it is structured data then it’s often stored in a table within a modern database, data warehouse or lakehouse. If it’s unstructured data, then it’s often stored as a vector in a namespace within a vector database.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

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

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

Knowledge Hut

AUGUST 16, 2024

Hadoop, Apache Spark, Data Visualization tools are a few of the Data Science skills necessary to become a Data Scientist. Hadoop As Data Scientists deal with huge volumes of data, sometimes the memory of the system might not be enough to carry out the processing.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

phData: Data Engineering

NOVEMBER 8, 2024

With the collective power of the open-source community, Open Table Formats remain at the cutting edge of data architecture, evolving to support emerging trends and addressing the limitations of previous systems. They also support ACID transactions, ensuring data integrity and stored data reliability.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Striim

OCTOBER 11, 2024

While legacy ETL has a slow transformation step, modern ETL platforms, like Striim, have evolved to replace disk-based processing with in-memory processing. This advancement allows for real-time data transformation , enrichment, and analysis, providing faster and more efficient data processing.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 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. It focuses on collecting, storing, and processing extensive datasets.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

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

Snowflake

APRIL 10, 2023

We transform unstructured data, such as text, images, and videos, into semantic fingerprints. From there, we can process information not unlike how humans do. The difference between semantha and humans is semantha processes data in seconds instead of months.” As a Snowflake partner, it was another natural choice.

Unstructured Data 59

Unstructured Data Manufacturing Insurance Government 59

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

Snowflake

APRIL 8, 2024

BigGeo BigGeo accelerates geospatial data processing by optimizing performance and eliminating challenges typically associated with big data. It deploys gen AI components as containers on Snowpark Container Services, close to the customer’s data.

Pipeline-centric 128

Pipeline-centric Food Healthcare Unstructured Data 128

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

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.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Datasets 98

Data Engineering Weekly

DECEMBER 25, 2023

Integrating AI into data workflows is not just a trend but a paradigm shift, making data processes more efficient and intelligent. Lake House Architectures: The New Frontier Lakehouse architectures have been at the forefront of data engineering discussions this year.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Monte Carlo

AUGUST 25, 2023

With pre-built functionalities and robust SQL support, data warehouses are tailor-made to enable swift, actionable querying for data analytics teams working primarily with structured data. Data lakes also typically decouple storage and comput e, which can enable cost savings while facilitating real-time streaming and querying.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw 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. These include: Structured data dependence: RPA solutions thrive on well-organized, predictable data.

Unstructured Data 59

Unstructured Data Government Data Validation Programming 59

Knowledge Hut

MAY 23, 2024

It uses batch processing to handle this flow of enormous data streams (that are unbounded - i.e., they do not have a fixed start and endpoint) as well as stored datasets (that are bounded). Python: Python is, by far, the most widely used data science programming language. Big Data Tools 23.

Data Science 52

Data Science MongoDB Programming Language Hadoop 52

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. Happy Learning!!!

Scala 98

Scala Hadoop Healthcare Big Data 98

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. Microsoft's Big Data strategy is broad and expanding rapidly.

Big Data 52

Big Data Unstructured Data Amazon Web Services Hadoop 52

Knowledge Hut

APRIL 23, 2024

Data Types Big Data Data Mining Big data refers to robust and complicated datasets that require a high level of expertise and tools for managing, processing, or analyzing. Traditional data processing techniques cannot be used.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Snowflake

NOVEMBER 29, 2023

Figure 2: Questions answered by precision medicine Snowflake and FAIR in the world of precision medicine and biomedical research Cloud-based big data technologies are not new for large-scale data processing. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 87

Metadata Healthcare Medical Data Storage 87

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

DoorDash Engineering

APRIL 26, 2023

Extraction of structured information Another strength of Generative AI is to understand unstructured data and parse it into a more structured format. This reduces manual effort and improves the accuracy and speed of data processing.

Food 98

Food Unstructured Data Deep Learning SQL 98

Striim

SEPTEMBER 11, 2024

Furthermore, Striim also supports real-time data replication and real-time analytics, which are both crucial for your organization to maintain up-to-date insights. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis. Are we using all the data or just a subset?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

SEPTEMBER 26, 2023

Because we have to often collaborate with cross-functional teams and are in charge of translating the requirements of data scientists and analysts into technological solutions, Azure Data Engineers need excellent problem-solving and communication skills in addition to technical expertise. What Does an Azure Data Engineer Do?

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Knowledge Hut

APRIL 23, 2024

Gathering data at high velocities necessitates capturing and ingesting data streams as they occur, ensuring timely acquisition and availability for analysis. Utilizing is related to the data processing and analyzing speed for gleaning useful insights. Customer data come in numerous formats.

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.

Data Engineer 75

Data Engineer Data Engineering Non-relational Database Engineering 75

The Modern Data Company

MAY 8, 2023

Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses. It stores structured and unstructured data, enables schema-on-read and schema-on-write, and supports real-time data processing and analytics.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses. It stores structured and unstructured data, enables schema-on-read and schema-on-write, and supports real-time data processing and analytics.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses. It stores structured and unstructured data, enables schema-on-read and schema-on-write, and supports real-time data processing and analytics.

Data Management 52

Data Management Management Data Lake Data Governance 52

Knowledge Hut

APRIL 23, 2024

Big Data certification course will support you in learning big data skills from the greatest mentors to help you build a career in big data. Top 10 Disadvantages of Big Data 1. Need for Skilled Personnel We see data in different forms; it can be categorized into structured, semi-structured, and unstructured data.

Big Data 52

Big Data Media Government Big Data Skills 52

U-Next

SEPTEMBER 9, 2022

The platform distributes Hadoop large data and analytics operations among computer cluster nodes, breaking them down into smaller workloads that may be handled in parallel. Hadoop can scale up from a single server to thousands of servers and analyze organized and unstructured data. . What is Hadoop in Big Data? .

Hadoop 40

Hadoop Big Data Management Unstructured Data 40

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? Misconception: Batch Processing Suffices Objection: Many AI/ML tasks can be handled with batch processing.

Healthcare 52

Healthcare Retail Algorithm Finance 52

Data Engineering Weekly

JUNE 4, 2023

link] Uber: Spark Analysers: Catching Anti-Patterns In Spark Apps One of the challenges in commoditizing data processing engines like Spark is that it requires an expert user to understand and operate this system. Many of the real-world data, all the way from medical images to astro monitoring, are unstructured data.

Data Engineer 52

Data Engineer Data Engineering Engineering Medical 52

Grouparoo

JANUARY 11, 2022

Typical applications are in scientific experimentation and observation processes where data consumers will not fully understand the nature of the data until after the completion of data processing and analysis. A data lake offers the ideal solution for storing such data of unknown relationships.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

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. Finally, kappa architectures are not suitable for all types of data processing tasks.

Data Integration 69

Data Integration Architecture Amazon Web Services Machine Learning 69