Cloudera

FEBRUARY 15, 2024

Seeing the future in a modern data architecture The key to successfully navigating these challenges lies in the adoption of a modern data architecture. The promise of a modern data architecture might seem like a distant reality, but we at Cloudera believe data can make what is impossible today, possible tomorrow.

Insurance 93

Insurance Banking Data Architecture Data Ingestion 93

Cloudera

SEPTEMBER 12, 2022

And second, for the data that is used, 80% is semi- or unstructured. Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. The post Chose Both: Data Fabric and Data Lakehouse appeared first on Cloudera Blog.

Unstructured Data 80

Unstructured Data Data Lake Data Architecture Data 80

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 examine a few.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Cloudera

AUGUST 21, 2024

The root of the problem comes down to trusted data. Pockets and siloes of disparate data can accumulate across an enterprise or legacy data warehouses may not be equipped to properly manage a sea of structured and unstructured data at scale.

Unstructured Data 70

Unstructured Data Business Intelligence Data Architecture Data Warehouse 70

Snowflake

NOVEMBER 2, 2023

And, since historically tools and commercial platforms were often designed to align with one specific architecture pattern, organizations struggled to adapt to changing business needs – which of course has implications on data architecture.

Data Lake 97

Data Lake Data Warehouse Cloud Unstructured Data 97

Cloudera

NOVEMBER 17, 2022

With CDP, HBL will manage data at scale through a centralized data lake, serving Pakistan, Sri Lanka, Singapore and other international territories. The bank will be able to secure, manage, and analyse huge volumes of structured and unstructured data, with the analytic tool of their choice. .

Banking 91

Banking Management Data Lake Professional Services 91

Towards Data Science

DECEMBER 4, 2023

Anyways, I wasn’t paying enough attention during university classes, and today I’ll walk you through data layers using —  guess what  —  an example. Business Scenario & Data Architecture Imagine this: next year, a new team on the grid, Red Thunder Racing, will call us (yes, me and you) to set up their new data infrastructure.

Data Engineer 81

Data Engineer Data Engineering Engineering Data Lake 81

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Education 65

Education Unstructured Data Data Lake Data Warehouse 65

Data Engineering Weekly

SEPTEMBER 18, 2024

Decoupling of Storage and Compute : Data lakes allow observability tools to run alongside core data pipelines without competing for resources by separating storage from compute resources. This opens up new possibilities for monitoring and diagnosing data issues across various sources.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Datasets 98

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The high-level architecture shown below forms the backdrop for the exploration. Luke: Let’s talk about some of the fundamentals of modern data architecture.

Data Lake 88

Data Lake Analytics Application Cloud Storage Architecture 88

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

DECEMBER 7, 2020

Leaders are moving to “segments of one,” defined as tracking and understanding individual behaviors across all touchpoints using the data to customize offers, products, or services to the individual customer.

Retail 65

Retail Unstructured Data Big Data Media 65

Data Engineering Weekly

MARCH 3, 2024

[link] AWS: Data governance in the age of generative AI The AWS Big Data Blog discusses the importance of data governance in the age of generative AI, emphasizing the need for robust data management strategies to ensure data quality, privacy, and security across structured and unstructured data sources.

Data Engineer 69

Data Engineer Data Engineering Pipeline-centric Engineering 69

phData: Data Engineering

NOVEMBER 8, 2024

Additionally, the optimized query execution and data pruning features reduce the compute cost associated with querying large datasets. Scaling data infrastructure while maintaining efficiency is one of the primary challenges of modern data architecture.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

AltexSoft

OCTOBER 25, 2021

This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. But a lot of data (by different estimations, 70 or 80 percent of all clinical data) remains unstructured , kept in textual reports, clinical notes, observations, and other narrative text.

Medical 52

Medical Healthcare Process Hospitality 52

Knowledge Hut

JUNE 23, 2023

Go for the best courses for Data Engineering and polish your big data engineer skills to take up the following responsibilities: You should have a systematic approach to creating and working on various data architectures necessary for storing, processing, and analyzing large amounts of data. What is COSHH?

Data Engineer 52

Data Engineer Data Engineering Engineering Non-relational Database 52

Silectis

JANUARY 3, 2021

Big Data Large volumes of structured or unstructured data. Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Snowflake

JANUARY 26, 2023

requires multiple categories of data, from time series and transactional data to structured and unstructured data. initiatives, such as improving efficiency and reducing downtime by including broader data sets (both internal and external), offers businesses even greater value and precision in the results.

Data Ingestion 52

Data Ingestion Manufacturing Unstructured Data Architecture 52

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. But while the modern data stack , and how it’s structured, may be evolving, the need for reliable data is not — and that also has some real implications for your data platform.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Monte Carlo

APRIL 1, 2021

Historically, many companies have used data catalogs to enforce data quality and data governance standards, as they traditionally rely on data teams to manually enter and update catalog information as data assets evolve. With the right approach, maybe we can finally drop the “ data swamp ” puns all together?

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

RandomTrees

SEPTEMBER 27, 2024

Data Factory, Data Activator, Power BI, Synapse Real-Time Analytics, Synapse Data Engineering, Synapse Data Science, and Synapse Data Warehouse are some of them. With One Lake serving as a primary multi-cloud repository, Fabric is designed with an open, lake-centric architecture.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

Monte Carlo

AUGUST 31, 2023

In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process. 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.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

MARCH 28, 2024

They work together with stakeholders to get business requirements and develop scalable and efficient data architectures. Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

ProjectPro

JUNE 6, 2015

At ProjectPro we had the pleasure to invite Abed Ajraou , the Director of the BI & Big Data in Solocal Group (Yellow Pages in France) to speak about the digital transformation from BI to Big Data. The goal of BI is to create intelligence through Data. The goal of BI is to create intelligence through Data.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

Monte Carlo

JUNE 14, 2023

Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Most data teams will be handling mostly structured data for analytical purposes making a data warehouse based data pipeline architecture a natural fit.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Databand.ai

JULY 19, 2023

This capability is useful for businesses, as it provides a clear and comprehensive view of their data’s history and transformations. Data lineage tools are not a new concept. In this article: Why Are Data Lineage Tools Important? Atlan Atlan offers a modern approach to data governance.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Snowflake

APRIL 5, 2023

With Snowflake’s support for multiple data models such as dimensional data modeling and Data Vault, as well as support for a variety of data types including semi-structured and unstructured data, organizations can accommodate a variety of sources to support their different business use cases.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

phData: Data Engineering

NOVEMBER 1, 2024

Strong data governance also lays the foundation for better model performance, cost efficiency, and improved data quality, which directly contributes to regulatory compliance and more secure AI systems.

Government 52

Government Data Governance Finance Metadata 52

Knowledge Hut

APRIL 26, 2024

Let's take a look at all the fuss about data science , its courses, and the path to the future. What is Data Science? In order to discover insights and then analyze multiple structured and unstructured data, Data Science requires the use of different instruments, algorithms and principles.

Data Science 52

Data Science Machine Learning Hadoop Algorithm 52

AltexSoft

AUGUST 29, 2023

Also, data lakes support ELT (Extract, Load, Transform) processes, in which transformation can happen after the data is loaded in a centralized store. A data lakehouse may be an option if you want the best of both worlds. Unstructured data sources. Data load with Snowpipe.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Snowflake

JUNE 28, 2023

Python Unstructured Data Processing (PuPr) – Unstructured data processing is now natively supported with Python. A few recent additions and libraries that will be landing soon include: langchain, implicit, imbalanced-learn, rapidfuzz, rdkit, mlforecast, statsforecast, scikit-optimize, scikit-surprise and more.

Python 52

Python Accessibility Accessible Pipeline-centric 52

Knowledge Hut

NOVEMBER 28, 2023

Computer science, mathematics, and statistics training are often required for data science positions. Data scientists do more than just model and process structured and unstructured data; they also translate the results into useful strategies for stakeholders. Average Data Scientist Pay vs.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Technical Data Engineer Skills 1.Python Knowing how to work with key-value pairs and object formats is still necessary.

Data Engineer 52

Data Engineer Data Engineering Engineering Generalist 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52