Cloudera

FEBRUARY 8, 2021

The vehicle-to-cloud solution driving advanced use cases. Airbiquity, Cloudera, NXP, Teraki, and Wind River teamed to collaborate on The Fusion Project whose objective is to define and provide an integrated solution from vehicle edge to cloud addressing the challenges associated with a fragmented machine learning data management lifecycle.

Manufacturing 105

Manufacturing Machine Learning Data Ingestion Electronics 105

Knowledge Hut

APRIL 23, 2024

Example of Data Variety An instance of data variety within the four Vs of big data is exemplified by customer data in the retail industry. Customer data come in numerous formats. It can be structured data from customer profiles, transaction records, or purchase history.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Snowflake

NOVEMBER 29, 2023

Data cloud technology can accelerate FAIRification of the world’s biomedical patient data. Flexibility to ensure that the data itself is interoperable and reusable across varied research, clinical and real-world use cases.

Healthcare 77

Healthcare Metadata Medical Data Storage 77

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Data pipeline architecture typically consisted of hardcoded pipelines that cleaned, normalized, and transformed the data prior to loading into a database using an ETL pattern. Data could now be extracted and loaded prior to being transformed for its ultimate use.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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. How Cloudera DataFlow works with Cloudera Data Platform (CDP)?

Hospitality 91

Hospitality Retail Kafka Data Ingestion 91

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? It becomes especially important to have a data storage and processing layer when you start to deal with large amounts of data and are holding that data for a long period of time and need it to be readily available for analysis.

Building 52

Building BI Data Lake Data Governance 52

Rockset

AUGUST 28, 2023

We founded Rockset to empower everyone from Fortune 500 to a five-person startup to build powerful search and AI applications and scale them efficiently in the cloud. The ability to scale apps efficiently in the cloud is what is going to allow enterprises to continue to leverage AI. We obsess about efficiency in the cloud.

Metadata 78

Metadata Unstructured Data SQL Database 78

AltexSoft

AUGUST 29, 2023

ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 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. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

MARCH 28, 2024

Azure Data Engineer Career Demands & Benefits Azure has become one of the most powerful platforms in the industry, where Microsoft offers a variety of data services and analytics tools. As a result, organizations are looking to capitalize on cloud-based data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. You can browse the data lake files with the interactive training material.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 13, 2023

They are experienced in practically every industry and have experience with blockchain, cloud, SAP, and AI solutions. Tech Mahindra Tech Mahindra is a service-based company with a data-driven focus. SAPC The HANA-in memory SQL server is the SAPC's primary big data tool; however, it also offers several analytics tools.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure, also known as Azure, is a well-known cloud computing service offered by Microsoft. It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. What is Azure Synapse?

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Monte Carlo

APRIL 24, 2023

With our new partnership and updated integration, Monte Carlo provides full, end-to-end coverage across data lake and lakehouse environments powered by Databricks. But remember that line from the introduction about the blurring line between data warehouses and data lakes? It works in both directions.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Throughout the industry, there are many different platforms that can be used for a data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

MAY 2, 2024

Spark is being used in more than 1000 organizations who have built huge clusters for batch processing, stream processing, building warehouses, building data analytics engine and also predictive analytics platforms using many of the above features of Spark. If not, it has to be used with some cloud-based data platform.

Scala 52

Scala Hospitality Healthcare Retail 52

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake BI Google Cloud 64

ProjectPro

FEBRUARY 8, 2023

For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. Another leading European company, Claranet, has adopted Glue to migrate their data load from their existing on-premise solution to the cloud. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. A dashboard that provides data in a graphical manner for in-depth study is the final product of this project.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Data Visualization Graphic representation of a set or sets of data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

U-Next

OCTOBER 27, 2022

Cloud computing is the term used to describe internet data storage and access. It doesn’t store any data on your computer’s hard drive and allows users to access data from faraway servers. Software experts overseeing a company’s cloud computing architecture are AWS solutions architects.

AWS 40

AWS Amazon Web Services Cloud Computing Cloud 40

Rockset

JULY 29, 2022

Google BigQuery BigQuery is Google’s data warehouse service and one of the first cloud data warehouses released to the public. However, the data via its streaming API insert isn’t available for two to three minutes. So, it’s not real-time data. The Snowpipe feature manages continuous data ingestion.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

ProjectPro

FEBRUARY 21, 2023

Vendor-Specific Data Engineering Certifications The vendor-specific data engineer certifications help you enhance your knowledge and skills relevant to specific vendors, such as Azure, Google Cloud Platform, AWS, and other cloud service vendors. Expertise in leveraging cloud platforms, data services, and solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 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 Engineering 52

Data Engineering Data Engineer Coding Project 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

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. It not only consumes more memory but also slackens data transfer.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 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 AWS Relational Database 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.

Engineering 52

Engineering NoSQL Programming Language Java 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. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 79

Engineering Raw Data Data Science Scala 79

Cloudera

SEPTEMBER 17, 2018

It also comes out of the box with a widely adopted, easy-to-use SQL Developer Workbench: Hue, that is specifically designed for the needs of the modern knowledge worker: No need to know _where_ the data resides. Hue can help you navigate to the right data no matter if the data is on-prem or in cloud.

Data Warehouse 52

Data Warehouse SQL Portfolio MySQL 52

ProjectPro

SEPTEMBER 1, 2016

To speed up the data processing all round, you need to speed up the HDFS file access. Hortonworks DataFlow is an integrated platform that makes data ingestion and processing easier and faster in Hadoop. Altiscale provides managed data processing services. DZone.com Hadoop is definitely faster with in-memory caching.

Hadoop 40

Hadoop Unstructured Data Big Data Portfolio 40

ProjectPro

APRIL 1, 2016

(Source: [link] ) Altiscale launches Insight Cloud to make Hadoop easier to access for Business Users. TechCrunch.com Altiscale, a company which has always been in the forefront about making the adoption of Hadoop easier and reducing complexity – recently launched a cloud service called Insight Cloud. March 15, 2016.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59