AltexSoft

FEBRUARY 11, 2023

Hands-on experience with a wide range of data-related technologies The daily tasks and duties of a data architect include close coordination with data engineers and data scientists. They also must understand the main principles of how these services are implemented in data collection, storage and data visualization.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

JUNE 26, 2023

Use Stack Overflow Data for Analytic Purposes Project Overview: What if you had access to all or most of the public repos on GitHub? As part of similar research, Felipe Hoffa analysed gigabytes of data spread over many publications from Google's BigQuery data collection. Learn Data Engineering the Smart Way!

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

DECEMBER 27, 2023

Software developers play an important role in data collection and analysis to ensure the company's security. Research and Development Private and government companies in Singapore hire software developers to conduct research and development to create innovative products and improve users' experience.

Medical 98

Medical Programming Language Amazon Web Services Entertainment 98

Knowledge Hut

DECEMBER 26, 2023

They collect and extract data from warehouses using querying techniques, analyze this data and create summary reports of the company's current standings. They suggest recommendations to management to increase the efficiency of the business and develop new analytical models to standardize data collection.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. Machine learning will link your work with data scientists, assisting them with statistical analysis and modeling.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

ProjectPro

FEBRUARY 21, 2023

Knowledge of the definition and architecture of AWS Big Data services and their function in the data engineering lifecycle, including data collection and ingestion, data analytics, data storage, data warehousing, data processing, and data visualization.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 27, 2023

This highly technical position requires apt education, certification, tech, soft skills, and experience.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Knowledge Hut

DECEMBER 29, 2023

They construct pipelines to collect and transform data from many sources. 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.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

MAY 3, 2024

7 Kafka stores data in Topic i.e., in a buffer memory. Spark uses RDD to store data in a distributed manner (i.e., cache, local space) 8 It supports multiple languages such as Java, Scala, R, and Python. It is a distributed collection of immutable things. Kafka keeps data in Topics, or in a memory buffer.

Kafka 98

Kafka Scala Java Amazon Web Services 98

ProjectPro

AUGUST 13, 2021

Predictive Analytics Predictive Analytics involves using data science methods to estimate the value of a quantity necessary for decision making. By implementing predictive analytics methods over the data collected in the past, companies can channelise themselves in the direction of rapid growth.

Machine Learning 40

Machine Learning Project Deep Learning Datasets 40

U-Next

AUGUST 8, 2022

The world demand for Data Science professions is rapidly expanding. Data Science is quickly becoming the most significant field in Computer Science. It is due increasing use of advanced Data Science tools for trend forecasting, data collecting, performance analysis, and revenue maximisation. data structure theory.

Data Science 40

Data Science Coding Programming Language Scala 40

Snowflake

JUNE 13, 2023

After testing, tesa recognized its team could handle data in each user’s preferred language with Snowpark, Snowflake’s developer framework for functional coding languages like Python, Java, and Scala. “Ensuring data quality and ease of data collection is currently at the top of our agenda, too.

Cloud 52

Cloud Manufacturing Datasets Scala 52

Data Engineering Podcast

JUNE 17, 2018

How do you prevent the user experience from suffering as a result of network congestion, while ensuring the reliable delivery of that data? Data collected in a user’s browser can often be messy due to various browser plugins, variations in runtime capabilities, etc.

Scala 100

Scala Kafka SQL Architecture 100

Knowledge Hut

FEBRUARY 15, 2023

Data analysis starts with identifying prospectively benefiting data, collecting them, and analyzing their insights. Further, data analysts tend to transform this customer-driven data into forms that are insightful for business decision-making processes. It is a web-based live analytics tool.

Data Cleanse 52

Data Cleanse Entertainment Business Intelligence Recruitment 52

Zalando Engineering

MAY 30, 2016

Hence, we decided to migrate the existing system to a new solution which is based on Spark and Scala. We will briefly sketch out our old solution, outline the pain points, and show how they were relieved by Spark and Scala. It is also written in Scala, a JVM-based language, which provides the type-safety we were missing before.

Scala 40

Scala Python Machine Learning Data Science 40

ProjectPro

DECEMBER 28, 2021

Moreover, Spark SQL makes it possible to combine streaming data with a wide range of static data sources. For example, Amazon Redshift can load static data to Spark and process it before sending it to downstream systems. Handling Late data Processing data on an event-by-event basis is a significant challenge in streaming.

Architecture 52

Architecture Kafka Java Scala 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. Another reason to use PySpark is that it has the benefit of being able to scale to far more giant data sets compared to the Python Pandas library.

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

APRIL 25, 2023

Top Data Ingestion Tools Some of the most popular Data ingestion tools used in the industry these days are mentioned below along with their prominent features: Apache Kafka: Written in Scala and Java, it delivers data with low latency and high throughput. It is useful for Big Data ingestion.

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Kafka 52

ProjectPro

NOVEMBER 22, 2021

PySpark runs a completely compatible Python instance on the Spark driver (where the task was launched) while maintaining access to the Scala-based Spark cluster access. Although Spark was originally created in Scala, the Spark Community has published a new tool called PySpark, which allows Python to be used with Spark.

Hadoop 52

Hadoop Python Datasets Metadata 52

Knowledge Hut

OCTOBER 24, 2023

Programming Languages Used for Data Science Visualization Projects Python R Matlab Scala Data Visualization Tools Businesses or many departments use data visualization software to track their own activities or projects. By seeing the visual representation of how prices change over time, future trends can be detected.

Project 52

Project BI Datasets Big Data 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. It ensures that the data collected from cloud sources or local databases is complete and accurate.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JUNE 28, 2016

Other than the speed required to ingest real time data and convert it into a common form for further analytics, scalability is a major challenge. Initially developed by LinkedIn for managing their internal data, it has steadily gained popularity. Written in Scala, Apache Kafka was open sourced in 2011.

Kafka 40

Kafka Systems Hadoop BI 40

AltexSoft

JUNE 7, 2021

The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. The framework provides a way to divide a huge data collection into smaller chunks and shove them across interconnected computers or nodes that make up a Hadoop cluster.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

U-Next

AUGUST 3, 2022

The following duties are frequently handled by Data Scientists, even though each data research situation is unique and their tasks change based on the project. Gathering data Any Data Science experiment must include data collecting since, without data to work with, one cannot be a Data Scientist.

Retail 52

Retail Data Science Computer Science Entertainment 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40