Cloudera

SEPTEMBER 12, 2022

A data fabric answers perhaps the biggest question of all: what data do we have to work with? Managing and making individual data sources available through traditional enterprise data integration, and when end users request them, simply does not scale — especially in light of a growing number of sources and volume.

Unstructured Data 74

Unstructured Data Data Lake Data Architecture Data 74

Monte Carlo

MAY 28, 2024

Data Transformation : Clean, format, and convert extracted data to ensure consistency and usability for both batch and real-time processing. Data Loading : Load transformed data into the target system, such as a data warehouse or data lake. Our promise: we will show you the product.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

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

Knowledge Hut

OCTOBER 30, 2023

This data and reports are generated and developed by Power BI developers. A Power BI developer is a business intelligence personnel who thoroughly understands business intelligence, data integration, data warehousing, modeling, database administration, and technical aspects of BI systems.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Knowledge Hut

DECEMBER 28, 2023

The certification path covers a comprehensive range of topics crucial for a successful career as an Azure Data Engineer: Data storage options like Azure Data Lake Storage and Azure SQL Data Warehouse Data processing solutions such as Azure Databricks and Azure Stream Analytics.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Databand.ai

AUGUST 30, 2023

In a DataOps architecture, it’s crucial to have an efficient and scalable data ingestion process that can handle data from diverse sources and formats. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. It can be set up as a security policy on all SQL Databases in an Azure subscription. One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. As a result, alternative data integration technologies (e.g., CRM platforms). public, private, hybrid cloud)? Computational Scalability.

Government 92

Government Hadoop Data Security Data Warehouse 92

ProjectPro

OCTOBER 6, 2021

Data Lake using Google Cloud Platform What is a Data Lake? Data Lake is a centralized area or repository for data storage. Here, data is stored, processed, and managed in its original format and can also be synthesized based on needs.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. That’s why there must be some sort of data replication, backup strategies, and failover mechanisms. Data security and privacy.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Ascend.io

JANUARY 2, 2024

Destination and Data Sharing The final component of the data pipeline involves its destinations – the points where processed data is made available for analysis and utilization. Typically, this data lands in storage systems like data warehouses or data lakes, awaiting further analysis by analytics and data science teams.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. PII data) of each data product, and the access rights for each different group of data consumers.

Architecture 124

Architecture Metadata Government Kafka 124

Silectis

JANUARY 3, 2021

Data Ingestion The process by which data is moved from one or more sources into a storage destination where it can be put into a data pipeline and transformed for later analysis or modeling. Data Integration Combining data from various, disparate sources into one unified view.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

phData: Data Engineering

SEPTEMBER 29, 2023

By utilizing data engineering best practices, a unified approach to comprehensive risk modeling and evaluation ensures consistency in the evaluation and comparison of data. Benefit: Data Engineering streamlines data integration and normalization, providing a precise and accurate risk assessment.

Data Engineering 52

Data Engineering Data Engineer Engineering Algorithm 52

Databand.ai

DECEMBER 13, 2022

1) Joseph Machado Senior Data Engineer at LinkedIn Joseph is an experienced data engineer, holding a Master’s degree in Electrical Engineering from Columbia University and having spent time on the teams at Annalect, Narrativ, and most recently LinkedIn. She holds a Computer Science degree, and has authored eight patents.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Databand.ai

JULY 19, 2023

The extracted data is often raw and unstructured and may come in various formats such as text, images, audio, or video. The extraction process requires careful planning to ensure data integrity. It’s crucial to understand the source systems and their structure, as well as the type and quality of data they produce.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Picnic Engineering

JULY 26, 2022

In addition, we have high development velocity, multiple antifragile tools to mitigate the downsides of centralization, and very high-quality analytics data across the business. Someone needs to look out for common operational data entities, and even when it is not feasible we need to at least make it visible.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

SEPTEMBER 21, 2023

The aim is to build reliable data pipelines that gather data from various sources and route it to the appropriate destinations, such as data lakes, data warehouses, or data lakehouses. We are the architects of data, ensuring its integrity, security, and accessibility.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

NOVEMBER 15, 2021

Companies like Yandex, CloudFare, Uber , eBay, Spotify have preferred Clickhouse owing to its performance, scalability, reliability, and security. It offers a fault-tolerant storage engine that prioritizes data security. It even has a simple web administration panel that is supplied directly from CouchDB!

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JANUARY 31, 2022

It also offers a unique architecture that allows users to quickly build tables and begin querying data without administrative or DBA involvement. Snowflake is a cloud-based data platform that provides excellent manageability regarding data warehousing, data lakes, data analytics, etc. What Does Snowflake Do?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 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. Having multiple data integration routes helps optimize the operational as well as analytical use of data.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52