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

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

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.

Systems 52

Systems Machine Learning Deep Learning Media 52

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. At the same time, the continuous growth of available data has led to information overload — when there are too many choices, complicating decision-making.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

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.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

Striim

SEPTEMBER 11, 2024

Here are six key components that are fundamental to building and maintaining an effective data pipeline. Data sources The first component of a modern data pipeline is the data source, which is the origin of the data your business leverages. Historically, batch processing was sufficient for many use cases.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Data Engineering Podcast

NOVEMBER 6, 2022

Summary A lot of the work that goes into data engineering is trying to make sense of the "data exhaust" from other applications and services. There is an undeniable amount of value and utility in that information, but it also introduces significant cost and time requirements. When is Snowplow the wrong choice?

Building 130

Building IT Metadata MongoDB 130

Knowledge Hut

FEBRUARY 29, 2024

Best website for data visualization learning: geeksforgeeks.org Start learning Inferential Statistics and Hypothesis Testing Exploratory data analysis helps you to know patterns and trends in the data using many methods and approaches. In data analysis, EDA performs an important role.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

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

Databand.ai

JUNE 8, 2023

By implementing an observability pipeline, which typically consists of multiple technologies and processes, organizations can gain insights into data pipeline performance, including metrics, errors, and resource usage. This ensures the reliability and accuracy of data-driven decision-making processes.

Data Pipeline 52

Data Pipeline Bytes Data Collection Raw Data 52

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.

Manufacturing 88

Manufacturing Pharmaceutical Healthcare Algorithm 88

Knowledge Hut

NOVEMBER 20, 2023

Not only individually but in conjunction with AI as one of the primary data sources used to train AI automation systems. By definition, IoT is a collection of physical objects integrated with software, sensors, and other devices for communicating and sharing data with different systems and devices over the internet.

Electronics 52

Electronics Utilities Architecture Computer Science 52

Knowledge Hut

MAY 3, 2024

For stream processing and transformations, one can utilize the Kafka Streams API, which offers T in ETL. Due to the fact that Spark enables users to retrieve, store, and alter data. Its interoperability with other kinds of systems, however, might appear to be extremely difficult. A continuous processing model is an outcome.

Kafka 98

Kafka Scala Java Amazon Web Services 98

Knowledge Hut

DECEMBER 27, 2023

Due to the inability to delete or amend the chain without network consensus, the data remains chronologically consistent. To manage orders, payments, accounts, and other transactions, you can utilize blockchain technology to establish an unchangeable or immutable ledger. How to Select a Blockchain Platform for your Business?

Programming Language 98

Programming Language Banking Utilities Algorithm 98

Striim

JULY 10, 2024

The utilization of predictive analytics has revolutionized nearly every industry, but perhaps none have experienced its transformative impact quite as profoundly as logistics. Predictive analytics in logistics involves utilizing statistical algorithms and machine learning techniques to analyze historical data.

Management 52

Management Transportation Machine Learning High Quality Data 52

Data Engineering Podcast

MAY 15, 2022

Summary Industrial applications are one of the primary adopters of Internet of Things (IoT) technologies, with business critical operations being informed by data collected across a fleet of sensors. What kinds of analysis are you performing on the collected data? Closing Announcements Thank you for listening!

Designing 100

Designing MongoDB AWS SQL 100

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Storage and Cost Big Data: Managing and storing Big Data requires specialized storage systems capable of handling large volumes of data. Additionally, the infrastructure investment and operational costs associated with storing and processing Big Data can be significant.

Big Data 52

Big Data Datasets Data Analysis Media 52

dbt Developer Hub

JANUARY 16, 2023

Imagine you were responsible for monitoring the safety of a subway system. This post demonstrates how the simple act of conducting tests by group can expand the universe of possible tests, boost the sensitivity of the existing suite, and help keep our data "on track". This feature is now available in dbt-utils.

Utilities 52

Utilities Datasets Data Collection Data 52

Engineering at Meta

JANUARY 27, 2023

This talk showcases Bifrost and Echo , which are the first networks to directly connect the US and Singapore and will support SGA, Meta’s first APAC data center. Millisampler data allows us to characterize microbursts at millisecond or even microsecond granularity.

Engineering 132

Engineering Software Engineer Software Engineering Transportation 132

Snowflake

MARCH 7, 2023

Andreas von Buchwaldt, Grant Mitchell, and Steve Varley of EY (2022) write, “Typically, the necessary data is not captured by legacy processes and systems. CEOs need to identify early the new internal business and impact data they will use to create a true measurement of progress and achievement.”

Transportation 71

Transportation Data Data Lake Retail 71

U-Next

FEBRUARY 26, 2023

Modern, dynamic dashboards use an HR analytics platform, which facilitates the easy combination of data from various systems and detailed exploration of this data directly within the dashboard. This data can be used to spark effective future efforts. If the data is already in Excel, go to the next step.

BI 97

BI Raw Data Recruitment Utilities 97

U-Next

MARCH 1, 2023

They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. Let’s take a look at Morgan Stanley interview question : What is data engineering? What is a data warehouse?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

JANUARY 23, 2024

The capacity of blockchain to store and manage data enables traceability, which is utilized to aid in creating and implementing technologies for intelligent farming and index-based crop insurance. It also leaves the entire system vulnerable to a cyber-attack. Weather extremes have an impact on agricultural and livestock quality.

Technology 52

Technology Food Insurance Data Collection 52

Knowledge Hut

MARCH 28, 2024

Now you might be thinking about what a data structure is, well it is the specialized way of storing and arranging data in the computer’s memory, allowing for efficient retrieval, manipulation and utilization. Learning data structures is like understanding computer language. Why are Data Structures Important?

Algorithm 52

Algorithm Java Utilities Data 52

Knowledge Hut

JULY 28, 2023

Hence, a systematic problem-solving technique used to identify underlying causes of incidents within IT systems and processes like RCA is needed. RCA, as an integral part of ITIL, focuses on identifying the underlying causes of incidents or problems within an organization's IT systems and processes.

Utilities 52

Utilities Data Collection Certification Systems 52

Knowledge Hut

NOVEMBER 15, 2023

Example 4: To utilize my background in mechanical engineering to improve the efficiency of manufacturing processes for a leading automotive company. Example 9: To utilize my experience in chemical engineering to develop new, environmentally-friendly products for a consumer goods company. Undergone data science course.

Finance 98

Finance Business Intelligence Database-centric Certification 98

Knowledge Hut

MARCH 22, 2024

It also allows organizations to leverage data collected from IoT devices, converting IoT data into actionable information. Because it is versatile and has robust features, Azure IoT is utilized for many applications in different industries.

Cloud Computing 52

Cloud Computing Utilities Cloud Transportation 52

Databand.ai

JULY 3, 2023

Data reliability vs. data validity Data reliability and data validity address two distinct aspects of data quality. In the context of data management, both of these qualities play a crucial role in ensuring the integrity and utility of the data at hand.

Data Validation 52

Data Validation Data Collection Data Machine Learning 52

Knowledge Hut

MARCH 28, 2024

Purpose and Utility Software metrics allow for the quantitative assessment of software quality attributes such as reliability, maintainability, and usability. This ensures that the data collected and analyzed will provide meaningful insights into the areas of interest, such as productivity, quality, or customer satisfaction.

Software Engineer 52

Software Engineer Software Engineering Data Collection Coding 52

ProjectPro

JUNE 28, 2016

To explain Apache Kafka in a simple manner would be to compare it to a central nervous system than collects data from various sources. This data is constantly changing, and is voluminous. This data can be anything from clickstream data, activity/ web logs, consumer data, etc.

Kafka 40

Kafka Systems Hadoop Big Data 40

Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. Data Collection Challenge. Factory ID.

Manufacturing 108

Manufacturing Data Warehouse Kafka Retail 108

Knowledge Hut

OCTOBER 29, 2023

Build Cardiovascular disease early detection system As the name suggests, this project is a simple one to get started with Azure Cognitive Services. Smart watches can help in data collection and then the same data can be fed into an application that is capable of sending alerts in case an outlier is detected.

Project 52

Project Hospitality Food Datasets 52

Knowledge Hut

NOVEMBER 20, 2023

This is not true for automated systems at the core. So, if you give a command that hasn’t been configured, the system won’t work. Etymologically, AI refers to the intelligence of a computer-controlled system that performs tasks commonly associated with humans. Learning AI systems learn from the data fed into them.

Manufacturing 52

Manufacturing Pharmaceutical Healthcare Finance 52

Knowledge Hut

JULY 31, 2023

In 2023, Business Intelligence (BI) is a rapidly evolving field focusing on data collection, analysis, and interpretation to enhance decision-making in organizations. The impact of business intelligence in network security systems: This topic investigates the role of business intelligence in enhancing network security systems.

Business Intelligence 52

Business Intelligence BI Data Mining Data Collection 52

Knowledge Hut

DECEMBER 29, 2023

There are many data science fields in which experts may contribute to the success of a business, and you can hone the abilities you need by specializing in data science subfields. Data Engineering and Warehousing The data is the lifeblood of every successful Data Science endeavor.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

JUNE 25, 2024

For those interested in studying this programming language, several best books for python data science are accessible. Top 8 Python Data Science Books for 2023 Python is one of the programming languages that is most commonly utilized in the field of data science. Let's have a look at some of the top ones.

Data Science 97

Data Science Python Hadoop Media 97

Knowledge Hut

APRIL 25, 2024

Big data can be summed up as a sizable data collection comprising a variety of informational sets. It is a vast and intricate data set. Big data has been a concept for some time, but it has only just begun to change the corporate sector. This results in a lack of management of data effectively.

Big Data 97

Big Data Entertainment Transportation Banking 97