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Migrating a Database? Consider These Factors First Database migration is usually performed with a migration tool or service. Migrating one database to another actually involves migrating the schemas, tables, and data; the software itself is not migrated. Whatever the reason for migration, before you start, explore the options and take these considerations into account. |
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Security Testing and Assessing Risk: A Slack Takeover with Shachar Schiff Thought leaders from the software community are taking over the TechWell Hub to answer questions and engage in conversations. Shachar Schiff, founder and principal consultant at BadTesting, hosted this Slack takeover and discussed assessing code coverage like a risk analyst, risk assessments outside security, and more. |
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Before Data Analysis, You Need Data Preparation One of the prerequisites for any type of analytics in data science is data preparation. Raw data usually has several shortcomings in structure, format, and consistency, so first it has to be converted to a usable form. These are some types of data preparation you can conduct to make your data useful for analysis. |
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Security Tips for App Development When companies develop applications they consider competitors and the market, but the most important aspect is cybersecurity. Developers need to release apps that don’t put consumers or their data in danger. Here are five tips that app developers should keep in mind to create and maintain the most secure apps possible. |
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Exploring Big Data Options in the Apache Hadoop Ecosystem With the emergence of the World Wide Web came the need to manage large, web-scale quantities of data, or “big data.” The most notable tool to manage big data has been Apache Hadoop. Let’s explore some of the open source Apache projects in the Hadoop ecosystem, including what they're used for and how they interact. |
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When to Use Different Types of NoSQL Databases Web-scale data requirements are greater than at a single organization, and data is not always in a structured format. NoSQL databases are a good choice for a larger scale because they're flexible in format, structure, and schema. Let’s explore different kinds of NoSQL databases and when it’s appropriate to use each. |
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Designing Data Models for Self-Documented Tests When testing applications, documenting and interpreting test results can be a challenge. Data models enable us to collect and process test data more dynamically and uniformly. To design effective data models for self-documented tests, there are three important things to consider: what to document, collect, and report. |
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Building Culturally Inclusive AI Models For us to build the most effective technology, we need to learn from our past and build our future with more comprehensive data sets with cultural intelligence. This means AI that recognizes your story, chatbots that speak to you more authentically, and smart assistants that have inclusive data about your ancestry. |
