Technology Articles

Cheat Sheet / Updated 05-15-2025

Whether you're just starting out with Excel or looking to sharpen your spreadsheet skills, this cheat sheet brings together some of the most practical tips you need for everyday use. It covers everything from quickly closing all your workbooks, to working smarter with templates, doing instant calculations, and even using advanced search with regular expressions. This guide is designed to help you save time, avoid common pitfalls, and discover handy Excel features you might not know exist. Let's make your Excel experience smoother and more enjoyable!

Cheat Sheet / Updated 05-12-2025

A geographic information system (GIS) is a software for making maps, analyzing data, and more. This cheat sheet tells you about what you can do with GIS, provides a handy guide to raster-based functions, gives you some key ideas to keep in mind about maps (relating to scales, projections, and datums), and the X, Y, and Z of GIS.

Cheat Sheet / Updated 05-12-2025

Word is one of the most used computer programs on the planet. Helping you to compose text is one of the things that computers do well, but that doesn't make the text-writing chore easier or imply that using Word is simple enough that professionals like you don't need help every now and then. So, enjoy this Cheat Sheet.

Article / Updated 04-28-2025

Today, applications can run anywhere — on-premises or in the cloud — and users can access them from anywhere, on virtually any device. Modern business trends including remote and hybrid work, distributed and extended workforces (such as contractors, partners, vendors, and other third parties), and the proliferation of cloud-hosted applications have led to the emergence of a new security perimeter: identity. An identity includes attributes such as user (or account) name, password (or passphrase or secret key), roles, access privileges, and historical context. This information identifies an individual or entity (such as a service, device, or application) in an organization’s systems and networks. As attackers increasingly target identities, organizations must stay ahead by implementing a comprehensive identity security program. In this article, we explain how the right approach to identity security can enhance your organization’s security posture, improve the employee experience, and deliver significant business benefits. Rather than developing exploits for system or application vulnerabilities, attackers can simply log in with stolen credentials. According to the 2024 Verizon Business Data Breach Investigations Report (DBIR), 68 percent of breaches are the result of credential theft (that is, the “human element”) from vectors including social engineering techniques (such as phishing, smishing, business email compromise, and pretexting) and brute-force dictionary attacks. A strong security posture is good for business When an organization falls victim to a ransomware attack or a data breach, normal business operations grind to a halt. It’s never “business as usual” when your employees, partners, and customers can’t access your critical applications and data because of a cyberattack. By improving network security and account hygiene, an identity security program can help organizations prevent breaches before they occur and respond quickly when compromised accounts are discovered, thus reducing the impact of any potential breaches. Don’t be the weak link in your supply chain security posture In our modern interconnected world, no business is an island, and the weakest link in your security posture may be one of your supply chain partners. According to research from BlueVoyant, more than four-fifths of organizations (81 percent) were impacted by supply chain attacks in 2024. Of course, supply chain attacks aren’t new — the 2013 Target data breach was the result of a compromised account belonging to a third-party maintenance vendor — but they have become more prevalent. More recently, the Change Healthcare (a subsidiary of UnitedHealth Group) attack in February 2024 cost nearly $9 billion in response efforts and assistance to affected healthcare providers. Every business has a supply chain and is a part of the supply chain itself — whether as an upstream supplier, downstream customer, or both. Third-party risk management has taken on renewed importance and can be a competitive differentiator when selecting new partnerships or renewing existing relationships. Yet many organizations struggle to manage third-party access to their systems and data. A strong identity security program can help an organization better manage guest accounts and monitor third-party activities, reducing the risk of data breaches caused by third-party access. Security is only strong if it is adopted While the login experience isn’t likely to top your employees’ list of factors impacting job satisfaction, it is a routine part of their daily work lives, and a poor experience can quickly cause user frustration. Struggling to remember different passwords, answering numerous multi-factor authentication (MFA) prompts, or calling the help desk to unlock their account — all before they’ve had their first cup of coffee — isn’t a great way to start the workday. Employees can benefit from an identity security program that provides quick and seamless access to their applications and devices, increasing productivity and reducing user frustration. A well-designed identity security program can also increase operational efficiency and decrease resource strain on IT and help desk teams by streamlining identity and access management (IAM) workflows such as account provisioning, permissions management, MFA enrollment, password resets, and reporting. It’s a win-win for everyone. By defining clear objectives and tying them to known business drivers and risks, organizations can ensure a strong identity security program that delivers measurable business value. To learn more about identity security and its business benefits, visit https://duo.com/ and download a free copy of Identity Security For Dummies.

Article / Updated 04-28-2025

For enterprises whose growth depends on the innovation of their developers and data scientists, success moves at the speed of their development environments. Efficiency, effectiveness, and the ability to build without friction — that’s what sets the pace. The question is simple enough: Do your developers and data scientists work their magic in cloud development environments (CDEs), or is their work bogged down by a legacy development environment? Read on to find out why local development environments and other traditional solutions may be holding back your developers, and how cloud development environments can set them free. How traditional development environments are lacking What are some of the ways the wrong development environment may be making your company’s progress sluggish? Local development environments: This was yesterday’s standard, with all developers managing their own environments on their own machines. All that local control gets in the way of getting ahead. It’s complicated and time-consuming to configure tools and dependencies on each individual environment. You wind up with inconsistencies that slow things down. And don’t even think about scaling this approach. Virtual desktop infrastructures (VDIs): VDIs help to centralize environments, but they’re often not really workable for development. They’re expensive and complicated to maintain. They also tend to suffer from sluggish performance, and that’s no way to keep developers happy. Shadow virtual machines (VMs): Developers may get around these issues with ad hoc VMs, but they end up creating different problems. “Shadow” solutions may be lacking in governance and are often overprovisioned. That makes them potential security risks, not to mention wasteful of resources. How cloud development environments can help A fully managed environment is the answer to the challenges of these more disjointed solutions from yesteryear. The CDE may be hosted in the cloud or via on-premises infrastructure, and it brings together all the necessary tools, libraries, and infrastructure needed for efficient development. It’s a development workspace that can be accessed from anywhere, not tied to a specific location or machine. It’s great for remote work, and because of its centralized infrastructure, it’s a lot more secure than storing code and data on developers’ laptops. Developers and data scientists can easily tap into it for coding applications and training machine learning (ML) models, getting up and running in minutes. Provisioning is automatic, so everything developers need is right there and ready to go. It can all be controlled from a centralized interface by authorized team members, ensuring only the right people can access code and data. And the compute and storage resources are easily scalable. How CDEs make developers more productive Traditional local development environments tend to be frustratingly slow when it comes to onboarding new developers or moving developers to new projects (and developers tend to take on new projects multiple times a year, of course). Provisioning environments can take days or even weeks, thanks to all the complexities of dependencies and the need for approvals. Meanwhile, if developers are off working in their own local environments, that also leads to problems requiring time-consuming troubleshooting. Mismatched environments are the enemy of success. What’s more, resource constraints can be a hangup in local development environments. CDEs, on the other hand, can be preconfigured, so developers just log in and get to work. Platform engineers can make global updates and ensure consistencies across the CDE. Configuration drift is no longer a problem. As for resource constraints, the cloud can fix that with high-performance resources that scale as needed. Developers can set up resource-intensive tasks such as ML model training in the cloud, and use their local laptops to get other work done in the meantime. Why cloud development environments provide better security Local development environments and various noncentralized alternatives can pose security threats, due to a lack of adequate governance and a hard-to-manage attack surface. Working with intellectual property and other sensitive data on developer laptops or unapproved VMs is risky. If developers need to pull sensitive data to their laptops for such things as ML model training, you’re tempting fate, because security problems don’t just hold developers back — they can set back the entire organization. CDEs, on the other hand, can live in a cloud environment or be centralized in on-premises infrastructure. They can be air-gapped if need be. Source code and data can stay in secure cloud or on-premise locations, along with any compute resources needed for dealing with them, so sensitive data never needs to leave the safety of home. Compliance teams aren’t fond of local environments because they’re tricky to monitor. CDEs, on the other hand, offer better monitoring and auditing capabilities, without getting in the way of the developers’ work. How CDEs save both money and time Face it — local development environments can be costly. Local hardware isn’t cheap, especially the high-end hardware needed for resource-intensive processes. But if your enterprise tries to trim those costs, developers are likely to be displeased. The reality is, CDEs not only provide a better developer experience and greater security, they also save money and time. Developers can use most cost-effective machines that are less powerful and longer-lasting, because the heavy lifting is happening in the CDE, not on the local machine. What’s more, CDEs can tap into automation to optimize resource utilization. Auto-start and auto-stop features mean unused environments aren’t sitting there wasting money. Bin-packing multiple developer workspaces onto a single VM can reduce infrastructure costs, too. And once again, helping developers be more efficient — by easing onboarding and transitioning, while banishing sluggish equipment — saves money, too. Time is, after all, money. If you can save hours and days and weeks of wasted developer time, you’ll get a whole lot more out of the money you’re paying them. To learn more about the benefits of CDEs, download your free Cloud Development Environments For Dummies, CoderTechnologies, Inc. Special Edition e-book.

Cheat Sheet / Updated 04-11-2025

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.