RandomTrees

FEBRUARY 6, 2024

Data engineering, the practice of collecting, transforming, and organizing data for analysis, is poised for a significant transformation with the advent of Generative Artificial Intelligence (Gen AI). Testing and Code Optimization: GenAI can automate testing processes by generating test cases, code, and synthetic data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

DataKitchen

FEBRUARY 21, 2023

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Data team morale is consistent with DataKitchen’s own research. We surveyed 600 data engineers , including 100 managers, to understand how they are faring and feeling about the work that they are doing.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

AltexSoft

SEPTEMBER 13, 2023

It points out the critical role that data quality plays in the outcomes you get from these algorithms. Watch our video about data preparation for ML tasks to learn more about this. This makes understanding how to create good prompts, also known as prompt engineering , very important for your projects. Customization.

Engineering 59

Engineering Hospitality Transportation Algorithm 59

Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools! What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Scott Logic

APRIL 22, 2024

It’s been around since 2017, and we don’t intend to go into a full review of its features here—only a month ago, Mike Morgan and Steve Conway from our Leeds office published a comparative review of three cloud BI solutions, including QuickSight here on the Scott Logic blog. Have Amazon succeeded?

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BI Software Engineer Software Engineering Algorithm 97

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? The answer is- by earning professional data engineering certifications! AWS or Azure?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

OCTOBER 4, 2023

Making sure data is able to land in real time and be accessed just as fast requires a “best fit” partitioning scheme. Check out our recent blog on integrating Apache Kudu on Cloudera Data Hub and Apache Impala on Cloudera Data Warehouse to learn how to implement this in your Cloudera Data Platform environment.

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Telecommunication Data Warehouse Java Manufacturing 87

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Pinterest Engineering

JUNE 13, 2023

Currently the loss weight for each task is equal, but during the data preparation stage, we apply various weight adjustments so that each training example is properly represented in the loss function. The loss function is captured below, where b = (1, … B) from B examples in the batch, and h = (1, … H) from H tasks.

Software Engineer 84

Software Engineer Software Engineering Utilities Architecture 84

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. In this article: Why are data testing tools important?

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

LinkedIn Engineering

DECEMBER 20, 2023

This blog post delves into the AutoML framework for LinkedIn’s content abuse detection platform and its role in improving and fortifying content moderation systems at LinkedIn. Most of these steps are automated using the AutoML framework, saving data scientists’ time and reducing the risk of errors.

Machine Learning 90

Machine Learning Datasets Algorithm Architecture 90

Databand.ai

AUGUST 30, 2023

Data Testing Tools: Key Capabilities and 6 Tools You Should Know Helen Soloveichik August 30, 2023 What Are Data Testing Tools? Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality.

Data Cleanse 52

Data Cleanse Data Validation Data Pipeline Datasets 52

Knowledge Hut

MAY 9, 2024

From Silicon Valley to Wall Street, from healthcare to e-commerce, data scientists are highly valued and well-compensated in various industries and sectors. According to Glassdoor, the average annual pay of a data scientist is USD 126,683. What is Data Science? They manage data storage and the ETL process.

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

Snowflake

JUNE 28, 2023

Since its launch two years ago, Snowpark has been empowering data scientists, data engineers, and application developers to streamline their architectures, accelerate development, and boost the performance of data engineering and ML/AI workloads on Snowflake.

Python 52

Python Accessible Accessibility Pipeline-centric 52

Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. Rockset is a real time analytics engine that allows SQL queries directly on raw data, such as nested JSON and XML.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

Cloudera

MARCH 31, 2021

In this first Google Cloud release, CDP Public Cloud provides built-in Data Hub definitions (see screenshot for more details) for: Data Ingestion (Apache NiFi, Apache Kafka). Data Preparation (Apache Spark and Apache Hive) . Google Cloud Storage buckets – in the same subregion as your subnets . Virtual Machines .

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Google Cloud Cloud Amazon Web Services Cloud Storage 92

Knowledge Hut

NOVEMBER 19, 2023

In this blog, we will explore the career paths of Artificial intelligence and what skills are most important to consider while taking this journey. There are various career options in artificial intelligence that you can consider if you want to be a machine learning engineer, data scientist, AI researcher or an AI ethicist.

Computer Science 52

Computer Science Programming Language Machine Learning Business Intelligence 52

Cloudera

APRIL 10, 2021

When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. While model training on small data can typically take minutes, doing the same on large volumes of data can take hours or even weeks.

Machine Learning 63

Machine Learning Data Science Deep Learning Utilities 63

Cloudera

DECEMBER 17, 2020

While it’s important to have the in-house data science expertise and the ML experts on-hand to build and test models, the reality is that the actual data science work — and the machine learning models themselves — are only one part of the broader enterprise machine learning puzzle. Laurence Goasduff, Gartner.

Machine Learning 81

Machine Learning Data Science Data Pipeline Raw Data 81

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Knowledge Hut

DECEMBER 7, 2023

AI has a plethora of uses, including chatbots, recommendation engines, autonomous cars, and even medical diagnosis. In this blog, I'll define the AI project life cycle and walk you through the steps, tools, and significance of the AI model lifecycle management process. Feature engineering often requires domain knowledge and creativity.

Machine Learning 52

Machine Learning Algorithm Medical Government 52

LinkedIn Engineering

DECEMBER 13, 2022

In this blog post, we share more details on how LinkedIn performs observational causal inference at scale using our Ocelot platform. We chose to bundle the functionality of data preparation with the causal modeling for the following reasons.�� We fine tuned Spark jobs to reduce the data preparation time and failure rate.

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Data Preparation Data Science Designing Data Pipeline 55

AltexSoft

FEBRUARY 21, 2023

This blog post will delve into the challenges, approaches, and algorithms involved in hotel price prediction. For machine learning algorithms to predict prices accurately, people who do the data preparation must consider these factors and gather all this information to train the model. OTAs and metasearch engines.

Hospitality 52

Hospitality Datasets Algorithm Machine Learning 52

Zalando Engineering

JUNE 9, 2022

Examples for said components are our input data preparation, marketing attribution model or an incremental profit forecast for our campaigns. These components are owned and developed by different cross-functional teams (applied science, engineering, product) within Performance Marketing.

Database 52

Database Coding Python AWS 52

Rockset

FEBRUARY 24, 2022

Teams looking to reduce operational burden often find a good fit in Kinesis, saving their engineering teams time on setup and maintenance. Your data source doesn’t contain type-enforcement at the column level. Performance engineering requires significant effort even after setup. I’ll do my best to evaluate it objectively!

AWS 52

AWS Amazon Web Services Kafka SQL 52

Confluent

JUNE 18, 2019

For this reason and others as well, many projects start using their database for everything, and over time they might move to a search engine like Elasticsearch or Solr. It involves many moving parts, from data preparation to building indexing and query pipelines. Moving data into Apache Kafka with the JDBC connector.

Architecture 94

Architecture Building Kafka Database-centric 94

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager. Aspire as a Cloudera Parcel, available in the latest 3.2

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Pharmaceutical Unstructured Data Electronics Metadata 46

Picnic Engineering

MAY 23, 2023

At Picnic, we understand the importance of efficient and accurate customer service, which is why we’ve turned to natural language processing techniques to automate the classification of customer feedback as you can read in this and this blog post.

Machine Learning 72

Machine Learning Algorithm Deep Learning Architecture 72

AltexSoft

AUGUST 25, 2021

Internet search engines are wonderfully helpful when auto-filling our queries, language translation has never been more seamless and correct, and advanced grammar checks save our reputation when we’re sending emails. There are two main steps for preparing data for the machine to understand. Feature engineering.

Process 139

Process Deep Learning Datasets Machine Learning 139

Cloudera

MAY 16, 2019

Some of the key trends we’ve both seen in the market are: Proprietary processing and infrastructure platforms cannot match the scale and innovation of the open-source infrastructure community, but every large enterprise analytics project needs multiple different engines to meet their goals.

Data Warehouse 40

Data Warehouse Government Data Preparation Data Governance 40

Rockset

SEPTEMBER 14, 2021

Rockset indexes the entire data stream so when new fields are added, they are immediately exposed and made queryable using SQL. We’ve also enabled the ingest of historical and real-time streams so that customers can access a 360 view of their data, a common real-time analytics use case. And, you can make that move today.

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Kafka SQL MongoDB Computer Science 52

U-Next

SEPTEMBER 7, 2022

People who are unfamiliar with unprocessed data often find it difficult to navigate data lakes. Usually, raw, unstructured data needs to be analyzed and translated by a data scientist using specialized tools. . As with data warehouses, processed data only requires the user to be familiar with the topic represented. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Cloudera

FEBRUARY 8, 2023

I was looking for some broken code to add a workshop to our Spark Performance Tuning class and write a blog post about, and this fitted the bill perfectly. appName( "Churn Analysis Data Preparation Test Harness" ) .getOrCreate() json('data/df_baseline') stayed_baseline.write.mode("overwrite").json('data/stayed_baseline')

Java 57

Java Datasets Coding Python 57

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

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AWS Scala Metadata Data Lake 98