Cloudera

JUNE 2, 2022

CDF-PC is a cloud native universal data distribution service powered by Apache NiFi on Kubernetes, ??allowing allowing developers to connect to any data source anywhere with any structure, process it, and deliver to any destination. This blog aims to answer two questions: What is a universal data distribution service?

Systems 103

Systems Data Lake Google Cloud Cloud 103

Data Engineering Podcast

JUNE 29, 2020

Summary We have machines that can listen to and process human speech in a variety of languages, but dealing with unstructured sounds in our environment is a much greater challenge. What are the unique challenges that you have faced in working with arbitrary sound data? What do you have planned for the future of the company?

Data Collection 100

Data Collection Management High Quality Data Metadata 100

Data Engineering Podcast

JULY 29, 2018

Summary With the attention being paid to the systems that power large volumes of high velocity data it is easy to forget about the value of data collection at human scales. What is Ona and how did the company get started? What are some examples of the types of customers that you work with?

Data Collection 100

Data Collection Kafka Data Warehouse Architecture 100

Analytics Vidhya

MARCH 5, 2023

Introduction Microsoft Azure HDInsight(or Microsoft HDFS) is a cloud-based Hadoop Distributed File System version. A distributed file system runs on commodity hardware and manages massive data collections. It is a fully managed cloud-based environment for analyzing and processing enormous volumes of data.

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Hadoop Data Collection Cloud Technology 246

Towards Data Science

APRIL 3, 2023

Building a Mental Model for Engineers and Anyone in Between Stream Processing can be handled gently and with care, or wildly, and almost out of control! By processing a smaller set of data, more often , you effectively divide and conquer a data problem that may otherwise be cost and time prohibitive.

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WeCloudData

OCTOBER 19, 2021

Next, in order for the client to leverage their collected user clickstream data to enhance the online user experience, the WeCloudData team was tasked with developing recommender system models whereby users can receive more personalized article recommendations.

Consulting 52

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WeCloudData

OCTOBER 19, 2021

Next, in order for the client to leverage their collected user clickstream data to enhance the online user experience, the WeCloudData team was tasked with developing recommender system models whereby users can receive more personalized article recommendations.

Consulting 52

Consulting Systems NoSQL Raw Data 52

Precisely

JULY 25, 2023

Organizations that run SAP can use Excel-to-SAP automation to do more with less, while also increasing agility and improving their SAP master data management process automation. We bring automation closer to the business users who own the data and the day-to-day processes that drive the business. Check out our free ebook.

Data Process 52

Data Process Process Data Data Integration 52

Rockset

DECEMBER 19, 2023

From his early days at Quora to leading projects at Facebook and his current venture at Fennel (a real-time feature store for ML), Nikhil has traversed the evolving landscape of machine learning engineering and machine learning infrastructure specifically in the context of recommendation systems.

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Systems Machine Learning Deep Learning Media 52

U-Next

OCTOBER 20, 2022

For instance, if you’re marketing premium spirits and only train your AI using data that mimics beer drinkers’ behavior, the results will be highly wrong and distorted. The data utilized to train the ML models is a major contributor to these biases. The source material is not the only way bias can enter data.

Data Collection 40

Data Collection Algorithm Datasets Data Analysis 40

Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. What is Data Aggregation?

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Process Data Mining Aggregated Data Portfolio 59

Data Engineering Podcast

JULY 20, 2020

Summary Wind energy is an important component of an ecologically friendly power system, but there are a number of variables that can affect the overall efficiency of the turbines. Michael Tegtmeier founded Turbit Systems to help operators of wind farms identify and correct problems that contribute to suboptimal power outputs.

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Systems Machine Learning Manufacturing Algorithm 100

Edureka

FEBRUARY 20, 2023

Principles of Quality Management System: Quality planning, assurance, control, and improvement are the four primary parts of quality management. To hold them to a high and consistent level, quality management monitors the activities, tasks, and processes (inputs) utilised to produce a product or service (outputs).

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Systems Management Manufacturing Food 52

Knowledge Hut

JANUARY 30, 2024

IT service lifecycle processes and stages are covered in five books that have been revised several times over the years. All professionals who want to take the exam for the ITIL 4 Foundation Certification must have a thorough understanding of the ITIL 4 framework and ITIL processes list.

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Process Certification Portfolio Telecommunication 52

The Pragmatic Engineer

OCTOBER 17, 2024

Storing data: data collected is stored to allow for historical comparisons. Benchmarking: for new server types identified – or ones that need an updated benchmark executed to avoid data becoming stale – those instances have a benchmark started on them.

Cloud 273

Cloud Metadata AWS Cloud Computing 273

Knowledge Hut

FEBRUARY 1, 2024

What is Data Cleaning in Data Science? Data cleaning is the process of identifying and fixing incorrect data. Various fixes can be made to the data values representing incorrectness in the data. The main advantage of the data pipeline is that each step is small, self-contained, and easier to check.

Data Science 52

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AltexSoft

JULY 27, 2021

You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. Personalization and recommender systems in a nutshell. Primarily developed to help users deal with a large range of choices they encounter, recommender systems come into play. Amazon, Booking.com) and.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

AltexSoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. No support for batch data. Connection layer.

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Knowledge Hut

JANUARY 18, 2024

For more information, check out the best Data Science certification. A data scientist’s job description focuses on the following – Automating the collection process and identifying the valuable data. A Python with Data Science course is a great career investment and will pay off great rewards in the future.

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Data Engineering Weekly

MAY 8, 2023

Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone. This data collection method was chosen because it was simple to deploy, with each employee responsible for their own receipts.

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U-Next

OCTOBER 16, 2022

From business transactions to scientific data, sensor data, pictures, videos, and more, we can and are handling a tremendous amount of information and data every day. The KDD process in data mining is used in business in the following ways to make better managerial decisions: . Data Selection and Integration: .

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Data Mining Process IT Raw Data 40

Data Engineering Podcast

APRIL 28, 2024

In order to simplify the integration of AI capabilities into developer workflows Tsavo Knott helped create Pieces, a powerful collection of tools that complements the tools that developers already use. What are the features and focus of Pieces that might encourage someone to use it over the alternatives?

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Building Data Lake High Quality Data Machine Learning 147

ProjectPro

NOVEMBER 30, 2021

ETL (Extract, Transform, and Load) Pipeline involves data extraction from multiple sources like transaction databases, APIs, or other business systems, transforming it, and loading it into a cloud-hosted database or a cloud data warehouse for deeper analytics and business intelligence.

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Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. RDD uses a key to partition data into smaller chunks.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

DECEMBER 21, 2021

Computer systems have limited capabilities without human guidance, and data labeling is the way to teach them to become “smart.” ” In this article, you will find out what data labeling is, how it works, which data labeling types exist, and what best practices to follow to make this process smooth as glass.

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

Confluent

FEBRUARY 21, 2019

It caused me to wonder if there was anything that I could do with my project HELK to apply some of the relationships presented in our talk, and enrich the data collected from my endpoints in real time. This is because the Create method allows a user to create a process either locally or remotely.

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Process Kafka SQL Datasets 83

Striim

SEPTEMBER 11, 2024

With data volumes and sources rapidly increasing, optimizing how you collect, transform, and extract data is more crucial to stay competitive. That’s where real-time data, and stream processing can help. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

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Cloudera

APRIL 13, 2022

If you’re AI-first, that means you have figured out how to leverage artificial intelligence to boost organizational agility so you can continuously adapt operational processes to deliver the right business outcomes. . Getting AI engines to deliver real-world benefits from gathering and interpreting intelligence requires lots and lots of data.

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Data Collection Algorithm Machine Learning Education 111

Snowflake

OCTOBER 2, 2024

These include security concerns and data privacy regulations, data access and management issues, and the complexities of implementing AI solutions into existing life sciences workflows. Additionally, there are high costs associated with implementing AI and maintaining a team of skilled professionals to develop and manage AI systems.

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Manufacturing Pharmaceutical Healthcare Algorithm 88

Striim

OCTOBER 11, 2024

Then, we’ll explore a data pipeline example and dive deeper into the key differences between a traditional data pipeline vs ETL. What is a Data Pipeline? A data pipeline refers to a series of processes that transport data from one or more sources to a destination, such as a data warehouse, database, or application.

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Data Pipeline MongoDB Unstructured Data Data Lake 52

Databand.ai

MAY 30, 2023

Data quality refers to the degree of accuracy, consistency, completeness, reliability, and relevance of the data collected, stored, and used within an organization or a specific context. High-quality data is essential for making well-informed decisions, performing accurate analyses, and developing effective strategies.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Snowflake

JANUARY 18, 2024

A fragmented resource planning system causes data silos, making enterprise-wide visibility virtually impossible. And in many ERP consolidations, historical data from the legacy system is lost, making it challenging to do predictive analytics. Ease of use Snowflake’s architectural simplicity improves ease of use.

Manufacturing 91

Manufacturing Unstructured Data Cloud Architecture 91

Cloudera

MAY 4, 2022

The availability and maturity of automated data collection and analysis systems is making it possible for businesses to implement AI across their entire operations to boost efficiency and agility. AI increasingly enables systems to operate autonomously, making self-corrections automatically as necessary.

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Insurance Retail Finance Medical 128

Precisely

FEBRUARY 29, 2024

Complexity is at the core of SAP automation challenges The core challenges to automating SAP processes essentially boil down to complexity. The business processes themselves are complex, as are the data objects associated with each SAP record. Let’s start with the complexity of the business processes.

IT 59

IT Process Data Collection Data Process 59

Snowflake

JULY 31, 2024

Academic medical centers (AMCs) are a critical keystone of healthcare systems worldwide. alone, there are more than 230 active AMCs , and a significant number are part of a health system. These platforms lack the scalability needed to manage the extensive data volumes and multiple concurrent research workloads essential for AMCs.

Medical 86

Medical Healthcare Insurance Hospitality 86

Knowledge Hut

MARCH 7, 2024

The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques. With the rise in opportunities related to Big Data, challenges are also bound to increase.

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