Technology Articles

Cheat Sheet / Updated 04-10-2025

The Microsoft Power Platform is a suite of applications that offers low-code and no-code development tools organizations can use to streamline and automate business processes. Collectively (and when integrated properly), the Power Platform suite of applications works together to support business transformation. Following is a description of the applications contained in the Power Platform, and some details about how each application functions as part of the suite: Dataverse: Starting your journey with each of the Power Platform applications requires one essential element: data. At the heart of the Power Platform is Dataverse, the common data service for storing and structuring relational data. Dataverse serves as the backbone for capturing and retaining user inputs across the platform's apps. Power Apps: The first step in the low-code/no-code journey to business automation is to create a mechanism for data entry. You can begin, for example, by using Power Apps to build an application that collects and manages data. Power Apps is often the primary tool businesses use to design custom applications that are tailored to their needs. Power Pages: Sometimes, you want the data entered with your Power Apps applications to be available for everyone to see, not just a few users. This is when you use Power Pages to design secure, data-driven external websites. The sites you create with Power Pages can display and collect information directly from Dataverse. Power Pages presents this data in a tabular format or as embedded reports and other media objects. Power BI: For data analysis, you use Power BI to transform data collected through custom apps created with Power Apps into interactive reports and insightful dashboards. Power Automate: You can use Power Automate to automate tasks and processes based on the data in Dataverse, which enhances productivity and efficiency across your organization.

Cheat Sheet / Updated 04-10-2025

Access makes managing data easy, enabling you to set up a database quickly, enter records into that database, and then use the data however you like. With Access, you can organize data into tables, design forms for editing and reports for presenting, and create queries for finding information!

Cheat Sheet / Updated 04-08-2025

Some readers like to thumb through a book and flag pages that they think are important. If that’s not you, we have you covered with this handy-dandy cheat sheet! This sheet contains all the important stuff you need to know about posting on Bluesky: rules for posting text, images, and videos and Bluesky’s community guidelines so your posts contribute to a healthy community.

Article / Updated 03-03-2025

In this article you will learn: The necessity of discovering and classifying all sensitive data Challenges of modern DSPM tools Solutions that DSPM tools provide Data is often shared and copied across multiple locations, making your most valuable business asset a security nightmare. It’s in your organization’s best interests to keep data as secure as possible, away from prying eyes, no matter where it resides. Doing so requires a structured and strong data security program backed by a powerful data security posture management (DSPM) solution. Modern DSPM is the next generation of data security technology, designed for the complexities of the hybrid cloud environments by tapping into the power of artificial intelligence (AI) and machine learning (ML) to continuously discover data and automate classification of sensitive information across known and unknown environments. The necessity of discovering and classifying all sensitive data Your sensitive data can’t be fully secure unless you’re able to effectively discover and classify every bit and byte of it, quickly and continually, and at scale, across your entire data footprint. That’s what modern DSPM excels at. Essential visibility — what data your enterprise has, how sensitive it is, and where it resides — is the key to security. Gaps in that visibility will stand in the way of a strong security posture. As data is discovered, modern DSPM classifies it automatically and precisely using AI and ML with advanced large language models. Modern DSPM solutions can discover and classify data types that are specific to your organization without any custom tuning. With data discovered and classified, you can then apply the appropriate security controls for keeping that data secure and keeping your organization in compliance with data protection regulations. Modern DSPM excels in both discovery and classification, which is why it’s critical for your data security program’s success. Challenges of modern DSPM tools Today’s data volumes and advanced technologies makes protecting your data a challenge, meaning legacy tools can’t keep up. You’ll find these problems when using a tool that’s not optimized for these challenges: Partially classified data: Legacy tools are designed with out-of-the-box classifiers, set up to only find what it’s looking for. Modern DSPM solutions find what you might not even know you should be looking for, such as unstructured sensitive documents specific to your organization. Discovery is slow: Data security requires rapid information, but legacy tools can’t keep up the pace. Scanning can take a long time because legacy tools don’t benefit from the AI and ML scanning techniques that a modern DSPM tool provides. Inaccurate classifications: Outdated tools tend to rely mainly on regular expressions and other older techniques to classify data. As a result, you need dedicated resources to manually write rules, tune the tools, and make sure classifications are accurate. Difficult to manage: With legacy tools, lots of agents and dedicated resources are needed to connect to datastores. That requires tons of work, and it is a monumental task to maintain. Solutions that DSPM tools provide DSPM, on the other hand, is made for modern data security challenges: Precision in classification and context: A modern DSPM solution applies AI and ML not only to detect common patterns, such as personal identifiers and financial data, but also to recognize proprietary, unstructured, or business-specific data with high precision. Scale and speed for today’s data environments: Precision alone isn’t enough for data that’s fast-moving and dispersed across SaaS, IaaS, and on-prem systems. Speed and scalability are essential. Modern DSPM tools operate agentlessly, scanning datastores quickly without disrupting business operations, providing rapid results, even across vast ecosystems. Actionable insights for remediation: Detecting risks is only the beginning. A powerful DSPM solution goes beyond visibility, offering actionable insights to address identified risks. Modern DSPM is the core that ties everything together and helps ensure the confidentiality, integrity, and availability of your data. You really can’t run a modern data security program without it. To learn more about modern DSPM solutions that support your business needs, download Modern DSPM For Dummies, Cyera Special Edition.

Article / Updated 02-20-2025

Artificial intelligence (AI) offers a lot of promise to companies, but deploying AI can be complex with many considerations and pitfalls. Data is the necessary asset to make AI work, and your organization is probably swimming in it. But how well-managed is your data? The answer hinges on whether your company will be successful in its AI efforts. Data management is the behind-the scenes workhorse that makes AI work. A robust management program allows data to be ingested from everywhere it needs to be, cleaned and transformed to enable AI model training, made easily available to users, and meticulously governed to ensure security, privacy, and compliance. In this article, we’ll explore several ways a data management platform can help with your AI efforts. Although these applications may differ, effective data management is always the necessary first step on which these solutions are built. Proprietary AI As your business scales, the number of receipts, invoices, contracts, and other printed documents scale, too. And when all those documents aren’t digitized, think of the number of hours it will take an employee to catalog it. It’s possible to use AI to automate this process. A proprietary engine scans and processes documents, extracts meaning from them, and outputs the data in a format that’s handy for reports, dashboards, and business intelligence apps. Some benefits of using proprietary AI to scan and process documents are: It can translate multiple languages. A large language model (LLM) can be trained to make sense of any specific document formats that your company may have. Accurate data helps with decision-making. Data can be extracted from third-party platforms, enrich it, validate it, and output it to dashboards accessible throughout the company. Identify issues with customers earlier. Algorithms aggregate and analyze user data, spotlighting any issues with customers early on to prevent customer churn. Or to spotlight when a loyal customer is ready to grow with your company. Retrieval augmented generation Things that work well in a controlled environment with a carefully curated data sample don’t always work in a real-world environment. One such situation is with retrieval augmented generation (RAG), the engine that LLMs rely on to give accurate facts. But if RAG is relying on legacy data that wasn’t prepared adequately, your AI solution is going to underperform. A data management program makes sure the basic, but vitally important, tasks are covered — data is cleaned, engineered, structured, and complete. Some tasks it can do are: Implement meta-intent branching for handling different types of queries. Develop verified quotes and see-it-in-source features for transparency. Monitor and balance token consumption. Improve data quality through semantic data scrubbing. Research and development Traditional research and development methods can be time consuming and expensive. Applying AI to the process can help reduce the cost and release products to the market faster. Reliable products help retain customers, boost the company’s reputation, and grow profit margin. High-quality data is needed to make it all work. A data management program can help with the following tasks: Automate manual processes. Automating helps to lower errors and inefficiencies, and accelerates quantitative research by navigating unstructured data. Business decisions get made faster. Verify and vet output. One system can generate formulas or prototypes for new products; a secondary one can automatically evaluate, compare, and check them for compatibility and other parameters. Enhance new network implementations and diagnostics. AI can create potential scenarios for the design and deployment of new systems. It can create hypotheses to pinpoint problems and suggest solutions. About the Book Wiley has recently published AI Data Management For Dummies, Keboola Special Edition. It includes insights from Snowflake and Capgemini that will help your organization integrate best practices and advanced technologies into your data strategy, what the future of AI development looks like, and more use cases. Download AI Data Management For Dummies, Keboola Special Edition by Andy Mott, Dan O’Riordan, and Rithesh Makkena to open the door to AI success.

Cheat Sheet / Updated 02-19-2025

Before you start using Instagram to promote your business, you may want to learn the lingo that Instagrammers use. Instagram doesn't like accounts that act spammy or over-engage in certain behaviors, so you need to become familiar with a number of restrictions as well as the appropriate image or video size to showcase your products and services. When you follow other Instagram profiles, you can share posts and even entire profiles in a direct message to another Instagram user.

Cheat Sheet / Updated 02-19-2025

Whether you're drafting text in Word, designing presentations in PowerPoint, analyzing data in Excel, or managing your inbox in Outlook, Microsoft Copilot can assist you every step of the way. With this cheat sheet, you'll have a handy reference to quickly understand how Copilot can enhance your productivity and streamline your tasks across various Microsoft 365 programs.

Cheat Sheet / Updated 01-13-2025

This cheat sheet gives you a rundown of some of the most useful features and apps so you can find what you need to customize your iPhone’s behavior. See how to get the most out of Siri (your iPhone’s virtual assistant), review some favorite apps for news and weather, and discover several of the most popular apps for multimedia.

Cheat Sheet / Updated 01-13-2025

So you’re using a Mac running macOS Sequoia? Good move! This Cheat Sheet warns you about six moves to avoid at all costs, gives you a handy reference of keyboard shortcuts that can save you time, teaches you how to navigate the Save As dialog using the Tab key, explains a straightforward protocol for backups, and tells you how to burn CDs from the Music app.

Cheat Sheet / Updated 01-05-2025

Six years after saying Windows 10 was the “last” version of Windows, Microsoft released Windows 11 on October 5, 2021. Although some people say it’s just Windows 10 with a new coat of paint, Windows 11 adds a few new features, removes some old ones, and changes the look and feel of Windows in some subtle ways. These tips help you work with the latest edition of Windows, Windows 11.