Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 102

Architecture Metadata Machine Learning Unstructured Data 102

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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 88

Insurance Banking Data Architecture Data Ingestion 88

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

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

Knowledge Hut

APRIL 23, 2024

Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis. It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 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

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

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

Zalando Engineering

JUNE 26, 2017

The immense explosion of unstructured data drives modern search applications to go beyond just fuzzy string matching, to invest in deep understanding of user queries through interpretation of user intention in order to respond with a relevant result set.

Architecture 40

Architecture Unstructured Data Machine Learning Data Ingestion 40

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 95

Kafka Hospitality Retail Data Ingestion 95

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. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

FEBRUARY 8, 2021

Future connected vehicles will rely upon a complete data lifecycle approach to implement enterprise-level advanced analytics and machine learning enabling these advanced use cases that will ultimately lead to fully autonomous drive.

Manufacturing 108

Manufacturing Machine Learning Data Ingestion Electronics 108

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

Data Pipeline 111

Data Pipeline Data Lake ETL Tools Unstructured Data 111

Data Engineering Weekly

JUNE 4, 2023

[link] KOHO: Handling Schema Evolution in the Data Pipelines at KOHO Schema management at the data ingestion service and the DLQ (Dead Letter Queue) pattern is emerging as the standard architecture pattern in event processing. Koho writes about its architecture to handle DLQ and schema management.

Data Engineer 52

Data Engineer Data Engineering Engineering Medical 52

Knowledge Hut

SEPTEMBER 26, 2023

Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands. Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types. Key Features of Databricks 1.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Snowflake

NOVEMBER 29, 2023

However, new technological approaches have unleashed the ability to scale data processing and computing in a secure, seamless and reliable manner, and move compute closer to the data. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 87

Metadata Healthcare Medical Data Storage 87

Rockset

AUGUST 28, 2023

Streaming first architectures are a necessary foundation for the AI era. Spin a Virtual Instance for streaming data ingestion. Never again worry about performance lags due to ingest spikes or query bursts. If you know SQL, you already know how to use Rockset. We obsess about efficiency in the cloud.

Metadata 78

Metadata Unstructured Data SQL Database 78

Snowflake

JUNE 5, 2024

Comparison of Snowflake Copilot and Cortex Analyst Cortex Search: Deliver efficient and accurate enterprise-grade document search and chatbots Cortex Search is a fully managed search solution that offers a rich set of capabilities to index and query unstructured data and documents.

Coding 89

Coding Building Management Government 89

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

Striim

AUGUST 28, 2024

Misconception: Complexity and Cost Objection: Implementing real-time data systems is complex and costly. The infrastructure required for real-time data ingestion, processing, and analysis can be significantly more expensive than batch processing systems.

Healthcare 52

Healthcare Retail Algorithm Finance 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

DareData

JULY 5, 2023

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 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

Cloudera

JUNE 4, 2018

That’s the equivalent of 1 petabyte ( ComputerWeekly ) – the amount of unstructured data available within our large pharmaceutical client’s business. Then imagine the insights that are locked in that massive amount of data. This enables data hub users to quickly access up-to-date content across the enterprise.

Pharmaceutical 45

Pharmaceutical Unstructured Data Electronics Metadata 45

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

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

AltexSoft

SEPTEMBER 21, 2023

These indices are specially designed data structures that map out the data for rapid searches, allowing for the retrieval of queries in milliseconds. As a result, Elasticsearch is exceptionally efficient in managing structured and unstructured data. Key components of the Elasticsearch architecture.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Cloudera

AUGUST 31, 2020

This helped the team identify the key architectural design elements of Hive LLAP, such as caching, and enabled their use cases and performance requirements. Today SMG can leverage tremendously more Data Science on both structured and unstructured data.

Management 66

Management Hadoop Data Warehouse Data Science 66

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. The ETL code for your data is automatically generated by AWS Glue when you specify your ETL process in the drag-and-drop job editor. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

JUNE 26, 2023

A complete end-to-end stream processing pipeline is shown here using an architectural diagram. The pipeline in this reference design collects data from two different sources, then conducts a join operation on related records from each stream, then enriches the output, and finally produces an average.

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

Rockset

JULY 29, 2022

However, the data via its streaming API insert isn’t available for two to three minutes. So, it’s not real-time data. Amazon Redshift Amazon Redshift cloud data warehouse is a fully-managed SQL analytics service. It analyzes structured and unstructured data from other warehouses, operational databases, and data lakes.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 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

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Hadoop architecture layers. Apache Hadoop.

Big Data 78

Big Data Data Analytics IT NoSQL 78