Mon.Feb 06, 2023

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What are Data Access Object and Data Transfer Object in Python?

Analytics Vidhya

Introduction A design pattern is simply a repeatable solution for problems that keep on reoccurring. The pattern is not an actual code but a template that can be used to solve problems in different situations. Especially while working with databases, it is often considered a good practice to follow a design pattern. This ensures easy […] The post What are Data Access Object and Data Transfer Object in Python?

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The evolution of Facebook’s iOS app architecture

Engineering at Meta

Facebook for iOS (FBiOS) is the oldest mobile codebase at Meta. Since the app was rewritten in 2012 , it has been worked on by thousands of engineers and shipped to billions of users, and it can support hundreds of engineers iterating on it at a time. After years of iteration , the Facebook codebase does not resemble a typical iOS codebase: It’s full of C++, Objective-C(++), and Swift.

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Isolated Python Environments using Docker

Analytics Vidhya

Introduction While working with multiple projects, there are chances of issues with versions of packages in python; for example, a project needs a new version of a package, and another requires a different version. Sometimes the python version itself changes from project to project. Managing these different python versions and different versions of packages is […] The post Isolated Python Environments using Docker appeared first on Analytics Vidhya.

Python 218
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5 Reasons Why You Need Synthetic Data

KDnuggets

Collecting and labeling data in the real world can be time-consuming and expensive. This data can also come with quality, diversity, and quantity issues. Fortunately, problems like these can be helped with synthetic data.

Data 108
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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How to Implement a Data Pipeline Using Amazon Web Services?

Analytics Vidhya

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary. Data engineers specialize in building and maintaining these data pipelines that underpin the analytics ecosystem.

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KDnuggets Survey: Benchmark with your peers on industry spend and trends

KDnuggets

KDnuggets and its partners have just released a Spend & Trends survey to provide you the opportunity to benchmark with your peers on how folks are spending and the mindsets around current trends.

IT 109

More Trending

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SQL and Python Interview Questions for Data Analysts

KDnuggets

Walking you through the most important SQL and Python technical concepts and four interview questions to practice for the Data Analyst position.

SQL 113
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Getting started with NLP using Hugging Face transformers pipelines

databricks

Advances in Natural Language Processing (NLP) have unlocked unprecedented opportunities for businesses to get value out of their text data. Natural Language Processing.

Process 96
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How to Setup a Simple ETL Pipeline with AWS Lambda for Data Science

Towards Data Science

How to setup a simple ETL pipeline with AWS Lambda that can be triggered via an API Endpoint or Schedule and write the results to an S3… Continue reading on Towards Data Science »

AWS 88
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5 Free Tools For Detecting ChatGPT, GPT3, and GPT2

KDnuggets

Top free tools to check research papers, thesis, assignments, documentation, and draft for AI content detection.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Easily Validate User-Generated Data Using Pydantic

Towards Data Science

How to us Pydantic to validate Excel data Photo by DeepMind on Unsplash Using Pydantic to validate Excel data As a data engineer, I frequently encounter situations where I have built pipelines and other automations based on user-generated data from Excel. Excel’s flexibility allows it to be used by a wide variety of users, but unfortunately, that flexibility leads to invalid data entering the pipeline.

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Dicing Godzillas (features with too many vertices)

ArcGIS

Vertices are the x,y coordinate pairs that define the shape of a feature, and the size of an individual feature.

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Could the Public Sector Solve the OSS Sustainability Challenges? by Colin Eberhardt

Scott Logic

The rapid rise in the consumption or usage of open source hasn’t been met with an equal rise in contribution – to put it simply, there are far more takers than givers, and the challenges created by this imbalance are starting to emerge. Most industries turn to open source for innovation and collaboration, however, the public sector instead looks for transparency and productivity.

IT 52
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2023, prepare to take-off

DareData

2022 [done] Hey guys, happy new year! This blog aims to disclose initiatives, achievements and adventures we had during the last year but also to share our difficulties. That is why we would very much appreciate questions, concerns or suggestions you might have around how to grow a data tech company like DareData Engineering. For those who have never heard about DareData, we are a high-end consulting “boutique” in the fields of data science and data engineering and we aim to become an inevitable

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Beyond the Hype: ChatGPT and why it has set the internet alight by Colin Eberhardt

Scott Logic

In this episode, I’m joined by my colleague, Oliver Cronk, and Chris Booth from NatWest for a lively discussion about the much-hyped ChatGPT. We discuss the origins of this technology and the recent advances that contributed to its success. From there, we look at the new discipline of prompt engineering, and how this approach has democratised access to cutting-edge AI.

IT 52
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Data Analytics Engineer- Is It Worth Pursuing in 2023?

ProjectPro

Did you know there are 40,000+ Data Analytics Engineer jobs in the United States as of Jan 2023? The role of a data analytics engineer is often overlooked but the impact is immeasurable. As technology continues to evolve, the roles in data science and big data need to evolve and, at times, merge together to achieve various business goals. Companies start looking for data professionals who have a thorough understanding of both the engineering and analytics aspects of the data stack.

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Data Warehouse Migration Best Practices

Monte Carlo

So, you’re planning a cloud data warehouse migration. A worthy quest to be sure. But be warned, a warehouse migration isn’t for the faint of heart. As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. In the old days, data warehouses were bulky, on-prem solutions that were difficult to build and equally difficult to maintain.

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Google Cloud Pub/Sub: Messaging on The Cloud

ProjectPro

With over 10 million active subscriptions, 50 million active topics, and a trillion messages processed per day, Google Cloud Pub/Sub makes it easy to build and manage complex event-driven systems. Google Pub/Sub provides global distribution of messages making it possible to send and receive messages from across the globe. Google Cloud Pub/Sub is a global, cloud-based messaging framework that has become increasingly popular among data engineers over recent years.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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What are HR Analytics and Metrics?

Edureka

The staff is a company’s most valuable asset; thus, the HR team must know its advantages and disadvantages. To maintain employee satisfaction — essential to a successful business—the HR staff must make important decisions. And these choices are frequently based on analytics and HR indicators. Organisations may use HR metrics and analytic s to assess the efficacy and efficiency of HR policy.

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Stemming in NLP- A Beginner's Guide to NLP Mastery

ProjectPro

The Internet is filled with information about almost everything. And this information is primarily available in the form of textual data. Many researchers are keen on finding interesting ways to mine and leverage this data. And one way to do that is to use Natural Language Processing (NLP) methods along with machine learning algorithms. This article will discuss one of the most popular methods, stemming, in NLP.

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Top Functional Testing Interview Questions (2023)

Edureka

We all use various software applications as part of our daily life. Even those not working in a company use a variety of applications to complete their routine activities. The use of apps for purchasing goods and services is so common that people of almost all strata of society use them regularly. These apps go through functional testing that the testers conduct.

Banking 52
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Why Data Integrity Is the Baseline for Innovation

Precisely

Data drives innovation in today’s global economy. Leading brands use advanced analytics and mobility data to understand consumers better and drive compelling customer experiences. Many other organizations leverage the power of location to evaluate risk, and respond more rapidly to their customer or member’s needs. Companies across all industries unify data from disparate sources for innovative AI initiatives that deliver proven value.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.

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How to get started with ChatGPT?

Edureka

OpenAI ChatGPT is a cutting-edge AI language model that is shaking up the world of conversational AI. The ability to generate human-like text responses makes it easier than ever to create chatbots, virtual assistants, and other conversational systems. This blog will show you exactly how to use ChatGPT to bring your own ideas to life. ChatGPT is based on the GPT (Generative Pretrained Transformer) architecture, which uses neural networks to process and generate text.

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JSON.parse () and JSON.stringify()

Cloudyard

Read Time: 1 Minute, 31 Second During this post we will discuss about how to handle JSON via javascript functions. Though there are many Javascript functions which we can leverage in our Snowflake stored procedure. But for this post we will discuss about two key JS functions to handle JSON data. Also Please note I am not well versed with javascript programming but thanks to other blogs who helped me to implement the below procedure.

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Azure Data Engineer Salary – How Much Can You Expect As An Azure Data Engineer?

Edureka

In today’s technological environment, where data and cloud computing are becoming more and more significant, an Azure Data Engineer is extremely important. Azure Data Engineers are in high demand due to the growth of cloud-based data solutions. In this article, we will examine the duties of an Azure Data Engineer as well as the typical pay in this industry.

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Why is it Important to Have Good Data Quality?

Acceldata

What is data quality and why is it important for enterprises to have good data quality?

IT 52
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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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Address Organizational Issues When Weaving the Data Mesh

Snowflake

We’ve all experienced the frustration of a bottleneck, like when in line for a chairlift at a ski resort. During the winter holidays, thrill seekers often face an infuriating wait for their ride up the mountain. Some seek new methods to get to the top, hence the rise of ski touring or “uphill skiing.” The mantra is “earn your turns.” Now think of the growing demand for data and insights.

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Link Multiple Data Clouds to Ascend

Ascend.io

If you’ve read this week’s release notes , you’ll have seen “Added ability to configure or override connection details at the Data Service level in BigQuery and Databricks Data Planes.” So what do we mean by that? Data Services Listing with BigQuery, Snowflake, and Databricks. Let’s first brush up on Ascend product terminology. Data Service – is a group of Data Flows.

Cloud 52
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Link Multiple Data Clouds to Ascend

Ascend.io

If you’ve read this week’s release notes , you’ll have seen “Added ability to configure or override connection details at the Data Service level in BigQuery and Databricks Data Planes.” So what do we mean by that? Data Services Listing with BigQuery, Snowflake, and Databricks. Let’s first brush up on Ascend product terminology. Data Service – is a group of Data Flows.

Cloud 52