Waitingforcode
MAY 7, 2025
One of the biggest changes for PySpark has been the DataFrame API. It greatly reduces the JVM-to-PVM communication overhead and improves the performance. However, it also complexities the code. Probably, some of you have already seen, written, or worked with the code like this.
Engineering at Meta
FEBRUARY 4, 2025
Here we explore initial system designs we considered, an overview of the current architecture, and some important principles Meta takes into account in making data accessible and easy to understand. Users have a variety of tools they can use to manage and access their information on Meta platforms. feature on Facebook.
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The Pragmatic Engineer
AUGUST 8, 2024
The below article was originally published in The Pragmatic Engineer , on 29 February 2024. I am re-publishing it 6 months later as a free-to-read article. This is because the below case is a good example on hype versus reality with GenAI. To get timely analysis like this in your inbox, subscribe to The Pragmatic Engineer. I signed up to try it out.
ProjectPro
JUNE 6, 2025
As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market. What Does Snowflake Do?
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End users fall into 4 different categories along the data literacy continuum when it comes to their skill level with data: Data challenged: Users have no-to-low levels of analytics skills or data access. Product managers need to research and recognize their end users' data literacy when building an application with analytic features.
Snowflake
FEBRUARY 27, 2025
Established in 2023, Snowflakes Startup Accelerator offers early-stage startups unparalleled growth opportunities through hands-on support, extensive ecosystem access and resources that surpass what other platforms provide.
ProjectPro
JUNE 6, 2025
Data preparation for machine learning algorithms is usually the first step in any data science project. It involves various steps like data collection, data quality check, data exploration, data merging, etc. This blog covers all the steps to master data preparation with machine learning datasets. Refer to the video below to know what it looks like.
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Access the Definitive Guide for a one-stop-shop for planning your application’s future in data. But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.
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Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late. In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.".
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Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
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Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.
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Organizations look to embedded analytics to provide greater self-service for users, introduce AI capabilities, offer better insight into data, and provide customizable dashboards that present data in a visually pleasing, easy-to-access format.
Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in. It integrates these digital solutions into everyday workflows, turning raw data into actionable insights.
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