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 64

Education Unstructured Data Data Lake Data Warehouse 64

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. Cloudera has supported data lakehouses for over five years. Better together.

Unstructured Data 74

Unstructured Data Data Lake Data Architecture Data 74

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

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

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Snowflake

APRIL 5, 2023

Two different data modeling approaches—dimensional data modeling and Data Vault—each have their own pros and cons. Modernizing a data warehouse with Snowflake Data Cloud is a smart investment that can provide significant benefits to businesses of all sizes, today more than ever as data models become ever more complex.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 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

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

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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 81

Data Lake Analytics Application Cloud Storage Architecture 81

Monte Carlo

AUGUST 31, 2023

Understanding the “rise of data downtime” With a greater focus on monetizing data coupled with the ever present desire to increase data accuracy, we need to better understand some of the factors that can lead to data downtime. We’ll take a closer look at variables that can impact your data next.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

AUGUST 29, 2023

The term data lake itself is metaphorical, evoking an image of a large body of water fed by multiple streams, each bringing new data to be stored and analyzed. Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 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

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Modern platforms like Redshift , Snowflake , and BigQuery have elevated the data warehouse model.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 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 Tools for accessing data warehouses and data mining devices have different functions.

Data Engineer 52

Data Engineer Data Engineering Engineering Generalist 52

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

Monte Carlo

APRIL 1, 2021

is whether to choose a data warehouse or lake to power storage and compute for their analytics. While data warehouses provide structure that makes it easy for data teams to efficiently operationalize data (i.e., And it’s an increasingly relevant one for modern data teams.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 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

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Edureka

FEBRUARY 9, 2023

Ingest data into one or more Azure services, including Azure Data Lake, Azure Storage, Azure SQL, and Azure DW, and process the data in Azure Databricks. Develop pipelines in ADF that extract, transform, and load data from sources such as Azure SQL, Blob storage, Azure SQL Data Warehouse, write-back tools, and others.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 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

Knowledge Hut

NOVEMBER 28, 2023

Data scientists do more than just model and process structured and unstructured data; they also translate the results into useful strategies for stakeholders. They must work on data architecture, collect and cleanse data from different sources, and conduct research. Average Data Scientist Pay vs.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JUNE 6, 2015

Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success. The goal of BI is to create intelligence through Data. But there is also Data Quality. So what is BI?

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure's Azure Synapse, formerly known as Azure SQL Data Warehouse, is a complete analytics offering. Designed to tackle the challenges of modern data management and analytics, Azure Synapse brings together the worlds of big data and data warehousing into a unified and seamlessly integrated platform.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Databand.ai

DECEMBER 13, 2022

We’d be remiss not to share that Joseph was a recent guest on Databand’s MAD Data Podcast , where he discussed ways to keep data systems from becoming unwieldy and shared tips for data teams to manage their data warehouses and keep data pipelines running reliably. You can also watch the video recording.

Data Engineer 52

Data Engineer Data Engineering Engineering AWS 52

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JUNE 9, 2021

Data Science looks into boosting the performance of a machine learning model. Data Engineering handles the entire data pipeline's optimization and efficiency for sourcing data from the data warehouse. It entails generating data visualizations and charts for analysis. Machine learning skills.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 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

ProjectPro

NOVEMBER 14, 2015

This data can be analysed using big data analytics to maximise revenue and profits. We need to analyze this data and answer a few queries such as which movies were popular etc. To this group, we add a storage account and move the raw data. Then we create and run an Azure data factory (ADF) pipelines.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

OCTOBER 20, 2021

Data Integration at Scale Most data architectures rely on a single source of truth. Having multiple data integration routes helps optimize the operational as well as analytical use of data. Experimentation in production Big Data Data Warehouse for core ETL tasks Direct data pipelines Tiered Data Lake 4.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

ProjectPro

MAY 31, 2021

Data Description: You will use the Covid-19 dataset(COVID-19 Cases.csv) from data.world , for this project, which contains a few of the following attributes: people_positive_cases_count county_name case_type data_source Language Used: Python 3.7 Access Solution to Data Warehouse Design for an E-com Site 4.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

SEPTEMBER 26, 2021

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. A Big Data Engineer also constructs, tests, and maintains the Big Data architecture.

Big Data 52

Big Data Data Engineer Data Engineering Engineering 52

Knowledge Hut

DECEMBER 26, 2023

Database-centric In bigger organizations, Data engineers mainly focus on data analytics since the data flow in such organizations is huge. Data engineers who focus on databases work with data warehouses and develop different table schemas. Let us now understand the basic responsibilities of a Data engineer.

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

Edureka

JULY 4, 2024

By letting you query data directly in the lake without the need for movement, Synapse cuts down the storage costs and eliminates data duplication. This capability fosters a more flexible data architecture where data can be processed and analyzed in its raw form.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40