KDnuggets

OCTOBER 3, 2024

Learn the data engineering tools for data orchestration, database management, batch processing, ETL (Extract, Transform, Load), data transformation, data visualization, and data streaming.

Data Engineering 135

Data Engineering Data Engineer Engineering Data 135

Confessions of a Data Guy

OCTOBER 3, 2024

I’ve been hacking around with tools and programming since Perl was a thing. I’ve worked the gambit of Data Platforms from large organizations to tiny startups, and all those in between. I’ve worked on Data Platforms that dropped ungodly amounts of money on SAP products, and places where we would build our own massive data […] The post Hosted (SaaS) vs DIY Data Tools appeared first on Confessions of a Data Guy.

Data 113

Data Programming Building Data Engineering 113

KDnuggets

OCTOBER 3, 2024

Want to create data science resumes that land interview calls and jobs? Avoid these common mistakes.

Data Science 119

Data Science Data 119

dbt Developer Hub

OCTOBER 3, 2024

If you haven’t paid attention to the data industry news cycle, you might have missed the recent excitement centered around an open table format called Apache Iceberg™. It’s one of many open table formats like Delta Lake, Hudi, and Hive. These formats are changing the way data is stored and metadata accessed. They are groundbreaking in many ways. But I have to be honest: I don’t care.

Metadata 86

Metadata Data Lake Data Storage Accessible 86

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

Software Engineer

Engineering at Meta

OCTOBER 3, 2024

Data for Good at Meta is open-sourcing the data used to train our AI-powered population maps. We’re hoping that researchers and other organizations around the world will be able to leverage these tools to assist with a wide range of projects including those on climate adaptation, public health and disaster response. The dataset and code are available now on GitHub.

Datasets 78

Datasets Government Banking Programming 78

Towards Data Science

OCTOBER 3, 2024

Three important lessons I have learned on my journey as data engineer and architect Continue reading on Towards Data Science »

Data Architecture 75

Data Architecture Architecture Data Science Data 75

Monte Carlo

OCTOBER 3, 2024

As a data analyst, you’re responsible for delivering trusted insights to your stakeholders. Unfortunately, that trust often comes at the cost of your time (and maybe a little sleep as well). The truth is, most analysts lose hours profiling their data, identifying thresholds, creating manual rules , and following up on data quality issues—all to make sure the data products they deliver to stakeholders meet six dimensions of data quality or more.

SQL 52

SQL Government Data Data Engineering 52

Striim

OCTOBER 3, 2024

In the fast-paced world of retail, the ability to harness data effectively is crucial for staying ahead. On September 18, 2024, at Big Data London, Morrisons shared its digital transformation journey through the presentation, “Learn How Morrisons is Accelerating the Availability of Actionable Data at Scale with Google and Striim.” Peter Laflin , Chief Data Officer at Morrisons, outlined the supermarket chain’s strategic partnership with Striim, a global leader in real-time data integ

Google Cloud 40

Google Cloud Cloud Retail Manufacturing 40

Monte Carlo

OCTOBER 3, 2024

As a data analyst, you’re responsible for delivering trusted insights to your stakeholders. Unfortunately, that trust often comes at the cost of your time (and maybe a little sleep as well). The truth is, most analysts lose hours profiling their data, identifying thresholds, creating manual rules , and following up on data quality issues—all to make sure the data products they deliver to stakeholders meet six dimensions of data quality or more.

SQL 52

SQL Government Data Data Engineering 52

Hevo

OCTOBER 3, 2024

Amazon Redshift is an online, petabyte-scale Data Warehouse service. It is dedicated to enterprise use, collecting large amounts of data and extracting analysis and insights from it. Redshift helps organizations query large DBs in real-time. Nonetheless, Redshift provides flexibility in performance as long as the cost aspect is well-handled to minimize cloud expenses.

AWS 40

AWS Data Warehouse Cloud IT 40

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Apache Airflow® is the open-source standard to manage workflows as code. It is a versatile tool used in companies across the world from agile startups to tech giants to flagship enterprises across all industries. Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.

Datasets

Knowledge Hut

OCTOBER 3, 2024

PMP certification validates your skills as a project manager and significantly enhances your career, similar to higher education but with a focus on practical experience. Before pursuing the certification, it’s crucial to weigh the advantages and disadvantages of project management. A table for advantages and disadvantages would be beneficial, as it helps clarify the pros and cons of the PMP process.

Certification 52

Certification Education Project SQL 52

Snowflake

OCTOBER 3, 2024

For the past couple years, generative AI has been the hot-button topic across my conversations with customers, prospects, partners and everyone in between. People want to know how they can harness the power of AI to become more innovative, efficient and competitive — and they want to do it as soon as possible. For many organizations, however, turning AI ideas into reality has proven elusive, with Harvard Business Review reporting that up to 80% of AI projects fail to make it into production.

Electronics 76

Electronics Portfolio BI Finance 76

Snowflake

OCTOBER 3, 2024

Natural language is rapidly becoming the bridge between human and machine communication. But hallucinations — when a model generates a false or misleading answer — continue to be the biggest barrier to the adoption of generative AI. Retrieval-augmented generation (RAG) allows enterprises to ground responses from LLMs in their specific organization’s data, reducing hallucinations, improving contextualized understanding and improving explainability.

Cloud 71

Cloud Data Governance Machine Learning Government 71