Towards Data Science

MAY 30, 2023

Comparing the performance of ORC and Parquet on spatial joins across 2 Billion rows on an old Nvidia GeForce GTX 1060 GPU on a local machine Photo by Clay Banks on Unsplash Over the past few weeks I have been digging a bit deeper into the advances that GPU data processing libraries have made since I last focused on it in 2019.

Data Engineering 97

Data Engineering Data Engineer Engineering Datasets 97

Cloudera

DECEMBER 14, 2021

They created a system to spread data across several servers with GPU-based processing so large datasets could be managed more effectively across the board. . LG Uplus , a South Korean telecommunications service provider, had just launched the world’s first 5G service in April 2019 but was struggling to commercialize it.

Transportation 111

Transportation Telecommunication Banking Data Lake 111

Knowledge Hut

MAY 2, 2024

According to the marketanalysis.com report forecast, the global Apache Spark market will grow at a CAGR of 67% between 2019 and 2022. billion (2019 – 2022). Dynamic nature: Spark offers over 80 high-level operators that make it easy to build parallel apps. count(): Return the number of elements in the dataset.

Hadoop 96

Hadoop Scala Datasets Java 96

Rockset

MARCH 1, 2023

But, these two functions directly compete for the available compute resources, creating a fundamental limitation that makes it difficult to build efficient, reliable real-time applications at scale. OLTP databases aren’t built to ingest massive volumes of data streams and perform stream processing on incoming datasets. Michael Carey.

Data Ingestion 144

Data Ingestion Database Architecture SQL 144

Netflix Tech

NOVEMBER 13, 2023

Practical use cases for speech & music activity Audio dataset preparation Speech & music activity is an important preprocessing step to prepare corpora for training. Nevertheless, noisy labels allow us to increase the scale of the dataset with minimal manual efforts and potentially generalize better across different types of content.

Datasets 96

Datasets Metadata Algorithm Architecture 96

KDnuggets

OCTOBER 24, 2019

In this post, you will see 3 different techniques of how to do Feature Selection to your datasets and how to build an effective predictive model.

Datasets 123

Datasets Building Machine Learning 123

Rockset

MARCH 18, 2024

Building a real-time, contextual and trustworthy knowledge base for AI applications revolves around RAG pipelines. What are the challenges building RAG pipelines? When you are building applications for consistent, real-time performance at scale you will want to use a streaming-first architecture.

Cloud 64

Cloud Building Metadata Kafka 64

DataKitchen

APRIL 13, 2021

DBT (Data Build Tool) — A command-line tool that enables data analysts and engineers to transform data in their warehouse more effectively. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Soda doesn’t just monitor datasets and send meaningful alerts to the relevant teams.

Consulting 121

Consulting Machine Learning Data Science Data Pipeline 121

Confluent

AUGUST 29, 2019

If Kafka is persisting your log of messages over time, just like with any other event streaming application, you can reconstitute datasets when needed. Here, we have three sample records moving over the “friends” topic in Kafka.

Kafka 55

Kafka Process Algorithm Cloud 55

AltexSoft

NOVEMBER 15, 2022

Read on to find out what occupancy prediction is, why it’s so important for the hospitality industry, and what we learned from our experience building an occupancy rate prediction module for Key Data Dashboard — a US-based business intelligence company that provides performance data insights for small and medium-sized vacation rentals.

Hospitality 52

Hospitality Building Datasets Machine Learning 52

Cloudera

DECEMBER 11, 2020

That compares to only 36 percent of customer interactions as of December 2019, which was before the pandemic impacted business, and only 20 percent in May 2018. It may not replace previous datasets, but alternative data offers another perspective to round out the historical information about an individual customer or business. .

Insurance 95

Insurance Unstructured Data Finance Machine Learning 95

dbt Developer Hub

OCTOBER 7, 2024

The image stuck out because, in one sense, a feature store is a bridge between the clean, consistent datasets and the machine learning models that rely upon this data. But, more interesting than the bridge itself is the massive process of coordination needed to build it. Why did we integrate/build this with Snowflake? ​

Data Pipeline 52

Data Pipeline Datasets Machine Learning Python 52

Knowledge Hut

JUNE 25, 2024

This book's publisher is "No Starch Press," and the second edition was released on November 12, 2019. The first edition was launched on February 25, 2015, and the second edition was issued on May 3, 2019. Explains how to build, tweak, and reliably deploy web apps online. Readers gave this book a rating of 4.36

Data Science 97

Data Science Python Hadoop Machine Learning 97

Picnic Engineering

JANUARY 9, 2024

Key Findings To test the models we ran experiments on a historic dataset consisting of customer item interactions within Picnic, as well as on the publicly available TaFeng dataset. The ground truth was the final basket in the dataset for each customer.

Machine Learning 91

Machine Learning Datasets Algorithm Systems 91

Knowledge Hut

DECEMBER 26, 2023

Python also finds its use in academic research and building statistical models adding to its versatility. Python provides frameworks/libraries like Scikit-learn, TensorFlow, PyTorch, Keras among others for building and validating ML or DL models in just 5-10 lines of code. Find interesting datasets, then figure out how to link them.

Data Science 92

Data Science Python Programming Language Portfolio 92

Cloudera

NOVEMBER 15, 2021

It aims to protect AI stakeholders from the effects of biased, compromised or skewed datasets. There are also proposals to move beyond bias-oriented framings of ethical AI, like the above, and towards a power-aware analysis of datasets used to train AI systems. Data scrutiny. Data fairness is one of the dimensions of ethical AI.

Unstructured Data 90

Unstructured Data Pipeline-centric Database-centric Entertainment 90

Precisely

FEBRUARY 27, 2023

In its 2019 Global CEO Outlook report , KPMG highlighted the importance of agility and resilience during times of uncertainty. That report was published in May of 2019, well before the COVID-19 pandemic emerged onto the world scene. All these datasets are closely interrelated, of course.

Process 52

Process Finance Datasets Designing 52

Precisely

FEBRUARY 27, 2023

In its 2019 Global CEO Outlook report , KPMG highlighted the importance of agility and resilience during times of uncertainty. That report was published in May of 2019, well before the COVID-19 pandemic emerged onto the world scene. All these datasets are closely interrelated, of course.

Finance 52

Finance Datasets Designing Coding 52

AltexSoft

AUGUST 18, 2021

Read on to know how to approach the airfare prediction problem and what we learned from our experience of building an price forecasting feature for the US-based online travel agency FareBoom. Preparing airfare datasets. To build an accurate model for price forecasting , we need historical data on flights and fares. “In

Algorithm 59

Algorithm Datasets R (Programming) Machine Learning 59

ProjectPro

NOVEMBER 30, 2021

Skills Required to Become a Deep Learning Engineer Deep Learning Engineer Toolkit Becoming a Deep Learning Engineer - Next Steps Deep Learning Engineer Jobs Growth Deep learning is the driving force of artificial intelligence that is helping us build applications with high accuracy levels.

Deep Learning 52

Deep Learning Engineering Machine Learning Programming Language 52

Netflix Tech

DECEMBER 17, 2019

Dump Processing Dumps are needed as transaction logs have limited retention, which prevents their use for reconstituting a full source dataset. Beyond Delta, DBLog is also used to build Connectors for other Netflix data movement platforms, which have their own data formats. Netflix specific streams are used as outputs such as Keystone.

MySQL 91

MySQL PostgreSQL Database Transportation 91

Netflix Tech

DECEMBER 17, 2019

Dump Processing Dumps are needed as transaction logs have limited retention, which prevents their use for reconstituting a full source dataset. Beyond Delta, DBLog is also used to build Connectors for other Netflix data movement platforms, which have their own data formats. Netflix specific streams are used as outputs such as Keystone.

MySQL 86

MySQL PostgreSQL Database Transportation 86

KDnuggets

AUGUST 22, 2019

As machine learning evolves, the need for tools and platforms that automate the lifecycle management of training and testing datasets is becoming increasingly important.

Machine Learning 71

Machine Learning Management Data Management Datasets 71

Data Engineering Weekly

JULY 30, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles, so you can quickly ship actionable, enriched data to every downstream team. link] All Things Distributed: Building and operating a pretty big storage system called S3.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Rockset

MAY 23, 2019

Our Solution is a Converged Index™ Rockset is approaching this problem with a radical solution: build indexes on all columns. A Converged Index allows analytical queries on large datasets to return in milliseconds. One of the design goals of Rockset is to absolutely minimize the amount of configuration the user needs to do.

Database 52

Database Datasets Media Algorithm 52

ProjectPro

FEBRUARY 25, 2022

Online fraud cases using credit and debit cards saw a historic upsurge of 225 percent during the COVID-19 pandemic in 2020 as compared to 2019. As per the NCRB report, the tally of credit and debit card fraud stood at 1194 in 2020 compared to 367 in 2019. lakh crore being syphoned off.

Machine Learning 52

Machine Learning Project Algorithm Datasets 52

Ascend.io

APRIL 20, 2023

Datasets and code are centralized into one big monolithic architecture. By splitting data into highly standardized and loosely coupled domains, data engineers can work with business stakeholders to build the data products they want and need in a highly shareable, accessible, and useful way. Why Is Data Mesh Important?

Government 52

Government Architecture Data Architecture Data Governance 52

ProjectPro

SEPTEMBER 16, 2021

Between 2019-02-01 and 2019-05-01, find the customer with the highest overall order cost. Also, assume that each first name in the dataset is distinct. Common Table Expressions (CTEs) are expressions used to build temporary output tables from which data can be obtained and used. What is meant by cte in SQL Server?

SQL 52

SQL MySQL MongoDB Data 52

AltexSoft

MAY 14, 2021

Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools. Distributed processing is used when datasets are just too vast to be processed on a single machine. What is Big Data analytics? Data ingestion.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

JANUARY 26, 2022

An analytics engineer is a modern data team member that is responsible for modeling data to provide clean, accurate datasets so that different users within the company can work with them. Data analysts are responsible for building reports and dashboards on top of pre-processed data and drawing out insights from it. Data roles compared.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

ProjectPro

AUGUST 5, 2021

If you’d like to build models that can converse with people and learn human language, you can work in the field of NLP (Natural Language Processing). Companies need AI specialists who can build and deploy scalable models to meet growing industry demands. Building a Telegram Bot 2. Dataset: Kaggle Resume Dataset 2.

Project 52

Project Datasets Machine Learning Deep Learning 52

ProjectPro

JANUARY 20, 2022

The ai and machine learning job opportunities have grown by 32% since 2019, according to Linkedin’s ‘ Jobs on the Rise ’ list in 2021. The ML engineer would be responsible for working on various Amazon projects, such as building a product recommendation system or, a retail price optimization system.

Machine Learning 52

Machine Learning Deep Learning Algorithm Programming Language 52

Cloudera

NOVEMBER 15, 2022

The first attempt to overcome this problem was the rollout of the HBOSS project in 2019. Unfortunately, when running the HBOSS solution against larger workloads and datasets spanning over thousands of regions and tens of terabytes, lock contentions induced by HBOSS would severely hamper cluster performance.

Database 76

Database Cloud Cloud Storage Architecture 76

Advancing Analytics: Data Engineering

JULY 2, 2019

We can see this on Monica Rogati’s Data Science Hierarchy of needs: The Data Science Hierarchy of Needs Pyramid, “THE AI HIERARCHY OF NEEDS” Monica Rogati Moving and storing data, looking after the infrastructure, building ETL – this all sounds pretty familiar.

Business Intelligence 52

Business Intelligence Data Engineering Data Engineer Engineering 52

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. The HR team will manage all of this data and generate datasets to be consumed by other users in the company like the marketing team.

Architecture 52

Architecture Data Lake Medical Datasets 52

DataKitchen

OCTOBER 5, 2022

A 2019 DataKitchen/Eckerson survey found that 79% of companies have more than three data-related errors in their pipelines per month. Data engineers are the people building pipelines, as well as doing data processing and data production. Do they know if integrations with other datasets are right?

Data Pipeline 69

Data Pipeline Engineering Datasets Data Engineering 69

Airbnb Tech

NOVEMBER 3, 2020

Ownership Prior to the Data Quality Initiative described in this post, data asset ownership was distributed mostly among product teams, where software engineers or data scientists were the primary owners of pipelines and datasets. The team also manages global datasets that don’t align well with any of the product teams.

Data Warehouse 52

Data Warehouse Scala Data Engineering Data Engineer 52