Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

AltexSoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. An example of a data lake architecture. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

JULY 29, 2022

The next step will be for telecom operators to continue tapping into these customer-centric data sources to develop novel ways of meeting customer needs that ultimately translate to an improved overall experience. This does not mean ‘one of each’ – a public cloud data strategy and an on-prem data strategy.

Data Architecture 91

Data Architecture Architecture Unstructured Data Government 91

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Each of these architectures has its own unique strengths and tradeoffs.

Data Lake 94

Data Lake Data Warehouse Cloud Unstructured Data 94

Cloudera

MAY 14, 2024

To attain that level of data quality, a majority of business and IT leaders have opted to take a hybrid approach to data management, moving data between cloud, on-premises -or a combination of the two – to where they can best use it for analytics or feeding AI models. Data comes in many forms.

Cloud 101

Cloud Data Governance Unstructured Data Data Architecture 101

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. 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. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

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 Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

AltexSoft

AUGUST 22, 2022

Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes. With these challenges in enterprise data management, there has to be an approach to overcoming them, right? The solution is called a data fabric.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

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? An AI Data Quality Analyst should be comfortable with: Data Management : Proficiency in handling large datasets.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. Where data flows, ideas follow.

IT 115

IT Unstructured Data Data Architecture Government 115

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 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. Better together.

Unstructured Data 77

Unstructured Data Data Lake Data Architecture Data 77

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. Data governance is the only way to ensure those requirements are met.

Government 52

Government Data Governance Finance Metadata 52

Striim

OCTOBER 11, 2024

These steps guarantee that data is accurate, reliable, and meaningful by the time it reaches its destination, making it possible for teams to generate insights and make data-driven decisions. This architecture can vary based on the needs of the organization and the type of data being processed.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

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 Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Cloudera

NOVEMBER 17, 2022

With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. Aqeel Ahmed Jatoi, Lead – Architecture, Governance and Control, Habib Bank Limited. Future-proof data capabilities. Smooth, hassle-free deployment in just six weeks.

Banking 87

Banking Management Data Lake Professional Services 87

Data Engineering Podcast

SEPTEMBER 14, 2020

In this episode Dale Kim shares how Hazelcast is implemented, the use cases that it enables, and how it complements on-disk data management systems. If you hand a book to a new data engineer, what wisdom would you add to it? What are the benefits and tradeoffs of in-memory computation for data-intensive workloads?

Process 100

Process Unstructured Data Metadata Data Engineer 100

Knowledge Hut

JANUARY 18, 2024

Roles and Responsibilities Finding data sources and automating the data collection process Discovering patterns and trends by analyzing information Performing data pre-processing on both structured and unstructured data Creating predictive models and machine-learning algorithms Average Salary: USD 81,361 (1-3 years) / INR 10,00,000 per annum 3.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

Monte Carlo

AUGUST 25, 2023

Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 23, 2024

Below are some of the differences between Traditional Databases vs big data: Parameters Big Data Traditional Data Flexibility Big data is more flexible and can include both structured and unstructured data. Traditional Data is based on a static schema that can only work well with structured data.

Big Data 52

Big Data Relational Database Data Datasets 52

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. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Sample of a high-level data architecture blueprint for Azure BI programs.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Data Engineering Weekly

MARCH 3, 2024

Part 2: Rippling's security data lakehouse and modular design DoorDash: Introducing DoorDash’s In-House Search Engine DoorDash writes about its in-house search engine to address scalability and efficiency issues identified with Elasticsearch's previous search architecture.

Data Engineering 67

Data Engineering Data Engineer Engineering Pipeline-centric 67

Knowledge Hut

MARCH 28, 2024

Data Engineer Career: Overview Currently, with the enormous growth in the volume, variety, and veracity of data generated and the will of large firms to store and analyze their data, data management is a critical aspect of data science. That’s where data engineers are on the go.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 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

Cloudera

APRIL 20, 2021

In today’s demand for more business and customer intelligence, companies collect more varieties of data — clickstream logs, geospatial data, social media messages, telemetry, and other mostly unstructured data. What is modern streaming architecture?

Kafka 97

Kafka Hospitality Retail Data Ingestion 97

Knowledge Hut

SEPTEMBER 28, 2023

My mission is to serve as the bridge between the intricacies of technology and the aspirations of our clients, harnessing the skills imperative for AWS Solution Architecture. Here are some AWS solution architect key skills and design principles for AWS architecture a. The basis for scalable and resilient applications is networking.

AWS 52

AWS Cloud Computing Architecture Cloud 52

Knowledge Hut

MARCH 26, 2024

Solutions Architect Careers: Overview Here's an overview of the demand and benefits of a career in Solutions Architecture: A. Cybersecurity Concerns: With the rise in cyber threats, organizations are prioritizing security in their IT architectures. Strong communication and stakeholder management skills.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 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? It provides context for data, making it easier to understand and manage.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Cloudera

FEBRUARY 8, 2021

Adding more wires and throwing more compute hardware to the problem is simply not viable considering the cost and complexities of today’s connected cars or the additional demands designed into electric cars (like battery management systems and eco-trip planning).

Manufacturing 110

Manufacturing Machine Learning Data Ingestion Electronics 110

Snowflake

NOVEMBER 29, 2023

The data is there, it’s just not FAIR: Findable, Accessible, Interoperable and Reusable. Defining FAIR data and it’s applications for life sciences FAIR was a term coined in 2016 to help define good data management practices within the scientific realm. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 87

Metadata Healthcare Medical Data Storage 87