Analytics Vidhya
FEBRUARY 6, 2023
This ensures easy […] The post What are Data Access Object and Data Transfer Object in Python? 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.
Scott Logic
APRIL 2, 2024
There’s just one last hurdle you’ve got to overcome: accessibility testing. Well, there is… and don’t call me Shirley… Make it automatic What if I told you that you could build accessibility testing into your automated test suites so that you can make sure your pages and components are accessible from the start? How do we do it?
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Towards Data Science
OCTOBER 30, 2024
Demystifying Azure Storage Account Network Access Service endpoints and private endpoints hands-on: including Azure Backbone, storage account firewall, DNS, VNET and NSGs Connected Network — image by Nastya Dulhiier on Unsplash 1. Defense in depth measures must be in place before data scientists and ML pipelines can access the data.
Edureka
JULY 19, 2024
Access control fundamentally secures systems by controlling and monitoring who can access resources or perform actions. Broken access control , on the other hand, is a vulnerability that is devoid of proper access control; Hence, the users could act or get access to resources to which they really should not have the authorization.
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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.
Cloudyard
NOVEMBER 1, 2024
However, due to compliance regulations, access to these fields needs to be restricted based on the user’s role. Snowflake provides several layers of data security, including Projection Policies , Masking Policies , and Row Access Policies , that work together to restrict access based on roles.
Monte Carlo
SEPTEMBER 17, 2024
It’s because data owners are responsible for ensuring the quality, security, and accessibility of a dataset across the entire organization. Then, data owners guide employees by defining and enforcing data access rules. Your company has mountains of data, and every department wants it. Let’s dive into how.
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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.
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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.
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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