Data Engineering Weekly

JUNE 30, 2024

Try For Free → Astasia Myers & Eric Flaningam: The rise of AI data infrastructure The article discusses the emergence of AI data infrastructure as a critical area for innovation. It is a good reminder to the data industry that we need to solve the fundamentals of data engineering to utilize AI better.

Data Engineer 102

Data Engineer Data Engineering Engineering Data Pipeline 102

Snowflake

SEPTEMBER 27, 2023

But all of this important data is often siloed and inaccessible or in hard-to-process formats, such as DICOM imaging, clinical notes or genomic sequencing. Healthcare organizations must ensure they have a data infrastructure that enables them to collect and analyze large amounts of structured and unstructured data at the point of care.

Healthcare 104

Healthcare Accessible Accessibility Hospitality 104

Cloudera

OCTOBER 5, 2023

By using data mesh, you move true data ownership to the business units, which improves the quality. Data now becomes a product. That facilitates data governance process automation which improves productivity as well as accuracy. Additionally, structured and unstructured data is often separate.

Data Governance 84

Data Governance Unstructured Data Government High Quality Data 84

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. What Should You Choose Between Big Data and Machine Learning?

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Monte Carlo

OCTOBER 10, 2024

As the use of AI becomes more ubiquitous across data organizations and beyond, data quality rises in importance right alongside it. After all, you can’t have high-quality AI models without high-quality data feeding them. Table of Contents What Does an AI Data Quality Analyst Do?

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Weekly

MARCH 3, 2024

Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 3) DataOPS at AstraZeneca The AstraZeneca team talks about data ops best practices internally established and what worked and what didn’t work!!!

Data Engineer 67

Data Engineer Data Engineering Engineering Pipeline-centric 67

Databand.ai

JULY 11, 2023

Data quality platforms can be standalone solutions or integrated into broader data management ecosystems, such as data integration, business intelligence (BI), or data analytics tools. In this article: Why Do You Need a Data Quality Platform?

Data Cleanse 52

Data Cleanse Telecommunication High Quality Data BI 52

Knowledge Hut

APRIL 23, 2024

Example of Data Variety An instance of data variety within the four Vs of big data is exemplified by customer data in the retail industry. Customer data come in numerous formats. It can be structured data from customer profiles, transaction records, or purchase history.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. But what does that mean for the roles of data engineers and data scientists going forward?

Database-centric 52

Database-centric Pipeline-centric Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights. Reach out today to learn how Monte Carlo’s data observability platform can help.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights. Reach out today to learn how Monte Carlo’s data observability platform can help.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

U-Next

SEPTEMBER 7, 2022

The various steps in the data management process are listed below: . Data collection, processing, validation, and archiving . Combining various data kinds, including both structured and unstructured data, from various sources . Ensuring catastrophe recovery and high data availability .

Data Management 52

Data Management Management Electronics Database 52

Monte Carlo

AUGUST 31, 2023

Not long after data warehouses moved to the cloud, so too did data lakes (a place to transform and store unstructured data), giving data teams even greater flexibility when it comes to managing their data assets. Rise of the Data Lakehouse Data warehouse or data lake?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

U-Next

SEPTEMBER 29, 2022

A structured data record consists of a very fixed field of data. Relational databases, spreadsheets, and other documents can contain this type of data. Moreover, it doesn’t help that data-driven businesses are becoming more and more difficult to operate. Step 2: Build data literacy and confidence .

Management 52

Management Unstructured Data Data Government 52

Netflix Tech

APRIL 26, 2022

ML algorithms can be only as good as the data that we provide to it. This post will focus on the large volume of high-quality data stored in Axion?—?our The Iceberg table created by Keystone contains large blobs of unstructured data. To achieve this, we rely on Machine Learning (ML) algorithms.

Metadata 78

Metadata Datasets Machine Learning Designing 78

ProjectPro

MAY 13, 2016

Hadoop and data warehouse technologies are optimized for various business requirements and can be used collectively, based on how they best fit the business use case. Using a Hadoop-only strategy can prove to be dangerous for any business’s data needs.

Data Warehouse 40

Data Warehouse Hadoop Unstructured Data Big Data 40

AltexSoft

MAY 27, 2021

The documents often come in semi-structured and unstructured data formats, which makes them difficult to process quickly and accurately. Infrrd is an innovative IDP-focused solution enabling high-quality data extraction from complex, unstructured documents.

Technology 64

Technology Process Insurance Medical 64

Knowledge Hut

JANUARY 25, 2024

Trustworthy Analytics: Reliable data supports accurate statistical analysis. Enhanced Visualization: Clean data leads to clearer data visualizations. Efficient Machine Learning: High-quality data is vital for training accurate ML models. What is the difference between data cleaning and data transformation?

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Knowledge Hut

JANUARY 24, 2024

In their quest for knowledge, data scientists meticulously identify pertinent questions that require answers and source the relevant data for analysis. Beyond their analytical prowess, they possess the ability to uncover, refine, and present data effectively. Will data scientists be replaced by AI ?

Database-centric 52

Database-centric Data Science Machine Learning Algorithm 52

AltexSoft

AUGUST 22, 2022

Data fabric vs data lake. In the data fabric vs data lake dilemma, everything is simple. Data lakes are central repositories that can ingest and store massive amounts of both structured and unstructured data, typically for future analysis, big data processing , and machine learning.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

FEBRUARY 21, 2023

With sufficient and quality data in place, ML becomes a valuable tool to forecast hotel deals. Data collection and preprocessing As with any machine learning task, it all starts with high-quality data that should be enough for training a model. So how exactly are hotel price prediction tools built?

Hospitality 52

Hospitality Algorithm Datasets Machine Learning 52

Edureka

FEBRUARY 7, 2023

They should also be comfortable working with a variety of data sources and types and be able to design and implement data pipelines that can handle structured, semi-structured, and unstructured data.

Data Engineer 52

Data Engineer Data Engineering Engineering Programming Language 52

ProjectPro

FEBRUARY 21, 2023

Microsoft introduced the Data Engineering on Microsoft Azure DP 203 certification exam in June 2021 to replace the earlier two exams. This professional certificate demonstrates one's abilities to integrate, analyze, and transform various structured and unstructured data for creating effective data analytics solutions.

Certification 52

Certification Data Engineer Data Engineering Engineering 52