ProjectPro

JUNE 6, 2025

This project offers initial insights into how Twitter uses a powerful two-tower model in its account recommendation pipeline to connect users with accounts aligned with their interests. How should I choose projects for my Data Science portfolio? This phase generates a set of potential recommendations per the user's behavior.

Portfolio 40

Portfolio Data Science Project Media 40

ProjectPro

JUNE 6, 2025

NumPy is often used in conjunction with other scientific computing libraries like SciPy, Pandas, and Matplotlib, creating a powerful ecosystem for data analysis, machine learning, and visualization. NumPy primarily deals with numerical data and may not be suitable for data types other than numbers.

Python 40

Python Process Deep Learning Medical 40

U-Next

AUGUST 17, 2022

Frequently, generalists are in charge of all phases of the analysis procedure, from data management through data analysis, because smaller firms won’t have to be concerned about engineering for scalability. They are frequently found in midsize businesses.

Data Engineer 52

Data Engineer Data Engineering Pipeline-centric Database-centric 52

The Modern Data Company

DECEMBER 29, 2022

And much of this involves finally harnessing data and new technologies to the fullest potential. Many of Deloitte’s Predictions Will Require Access to Real-time Data Analysis The report lists several areas where consumer demand will shift banking products. DataOS is the world’s first operating system.

Banking 52

Banking Pipeline-centric Building Finance 52

RandomTrees

SEPTEMBER 27, 2024

Data Factory, Data Activator, Power BI, Synapse Real-Time Analytics, Synapse Data Engineering, Synapse Data Science, and Synapse Data Warehouse are some of them. With One Lake serving as a primary multi-cloud repository, Fabric is designed with an open, lake-centric architecture.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Assess the needs and goals of the business.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

Workfall

AUGUST 29, 2023

Python is widely used in web development, data analysis, artificial intelligence, automation, scientific computing, and more, making it a go-to choice for developers worldwide. With its global reach and customer-centric approach, Amazon remains a top choice for online shopping worldwide. How to Execute Linux Commands in Python?

Python 93

Python Pipeline-centric Programming Language Electronics 93

AltexSoft

JUNE 7, 2021

Cassandra excels at streaming data analysis. Data access options. There are other tools like Apache Pig and Apache Hive that simplify the use of Hadoop and HBase for data experts who typically know SQL. It also provides tools for statistics, creating ML pipelines, model evaluation, and more. Spark limitations.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

SEPTEMBER 26, 2023

Key Features of Azure Synapse Here are some of the key features of Azure Synapse: Cloud Data Service: Azure Synapse operates as a cloud-native service, residing within the Microsoft Azure cloud ecosystem. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Striim

JULY 16, 2024

Dynamic Scheduling to Streamline Operations Dynamic scheduling, facilitated by AI and real-time data analysis, revolutionizes airline operations by continuously optimizing flight schedules based on current conditions. American Airlines Uses Real-Time Data to Supercharge Customer Journeys Want to see Striim’s impact in action?

Pipeline-centric 52

Pipeline-centric Algorithm Transportation Data Integration 52

Knowledge Hut

JULY 3, 2023

Data ingestion is the method of streaming a high volume of data from various different origins to your system. Due to the data ingestion process, you can perform various operations like data analysis, dashboarding and other analytical and business tools.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

Knowledge Hut

DECEMBER 26, 2023

By reusing and recombining capabilities to scale across business problem statements, scalability contributes to solving scarcity and collection issues of quality data. To use cloud-enabled and network-enabled edge devices and centralized data center capabilities to apply artificial intelligence to critical missions.

Data Science 52

Data Science Database-centric Pipeline-centric Data Mining 52

Ascend.io

SEPTEMBER 14, 2023

Data engineers can find one for almost any need, from data extraction to complex transformations, ensuring that they’re not reinventing the wheel by writing code that’s already been written. In dynamic teams, where multiple stakeholders may interact with code or data pipelines, this readability becomes even more crucial.

Data Engineer 52

Data Engineer Data Engineering Python Engineering 52

Databand.ai

DECEMBER 20, 2022

Follow Cassie on LinkedIn 3) Julia Silge Software Engineer at Posit PBC Julia is a tool builder, author, international keynote speaker, and real-world practitioner focusing on data analysis, machine learning, and MLOps. Eric is active on GitHub and LinkedIn, where he posts about data analytics, data science, and Python.

Data Analytics 52

Data Analytics Google Cloud Data Mining Data Science 52

Knowledge Hut

JUNE 26, 2023

Application Management Application management expertise is crucial in an Azure-centric ecosystem. Experience with Azure Kubernetes Service (AKS), Azure Container Instances (ACI), & Azure DevOps pipelines can help achieve this skill. Cloud Security Engineer : The security of cloud infrastructure is more important than ever before.

Cloud Computing 52

Cloud Computing Certification Pipeline-centric Database-centric 52

Knowledge Hut

FEBRUARY 6, 2024

Analytics is used to examine the data that an application has collected. This collection of tools is mostly used to conduct analysis and produce insightful reports. Although there are many technologies available for data analysis, a few are widely utilized in the DevOps sector.

Pipeline-centric 52

Pipeline-centric Database-centric Manufacturing AWS 52

AltexSoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. Data analysis.

Big Data 52

Big Data Data Process Process Hadoop 52

Knowledge Hut

JANUARY 30, 2024

Machine Data: For IoT applications, sensor data extraction is used to collect information from devices, machinery, or sensors, enabling real-time monitoring and analysis. Customer Interaction Data: In customer-centric industries, extracting data from customer interactions (e.g.,

Database-centric 52

Database-centric ETL Tools Data Mining Data Cleanse 52

Knowledge Hut

APRIL 19, 2023

These applications fulfill various purposes like word processing, data handling, data analysis, and much more, saving the time and resources that would be utilized manually. Software developers responsible for developing this software must be well-familiar with front-end, back-end, database management, and data pipelines.

Database-centric 52

Database-centric Entertainment Education Pipeline-centric 52

Knowledge Hut

NOVEMBER 15, 2023

Career Objective for Data Scientist Role resumecatstatic.com Example 1: I am a data science professional with experience in data analysis, machine learning, and predictive modeling. I am passionate about data and its potential to impact business decisions. Near to completing Cloud Computing Course.

Finance 98

Finance Certification Database-centric Business Intelligence 98

Knowledge Hut

MARCH 30, 2023

It employs historic data, analysis of metrics, and centralized reflection of operations to achieve the same. The PPM methodology and tools should also work towards building a portfolio-centric culture with processes being continuous and adaptable to be successful.

Portfolio 52

Portfolio Process Project Management 52