Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• 5 reasons to use AI and machine learning in a data warehouse

  Using AI and ML in a data warehouse gives the whole organization a single source of truth that can align decision making and foster better insights. Continue Reading

• Evaluate 8 of the top embedded analytics tools

  Selecting the right embedded analytics tool for your organization can be difficult. Use general criteria to evaluate eight of the top options and decide if one is the right fit. Continue Reading

• Collaborative business intelligence helps users connect data dots

  Social BI enables users to interact with their organization's data -- and data experts -- in applications where they already collaborate and work. Continue Reading

• AR and VR data visualizations offer promising future

  AR and VR data visualizations offer a new perspective to capture patterns and trends in complex data sets that traditional data visualizations struggle with. Continue Reading

• 10 top data discovery tools for insights and visualizations

  Data discovery can use sampling, profiling, visualizations or data mining to extract insights from data. Choose from 10 of the top platforms in the market that best fit the user base. Continue Reading

• The top augmented analytics tools vendors are offering

  Augmented analytics tools play a crucial role in providing users of all technical skills levels access to AI and analytics daily. Consider 10 of the top options available.Continue Reading

• What is data preparation? An in-depth guide

  Data preparation is the process of gathering, combining, structuring and organizing data for use in business intelligence, analytics and data science applications, as explained in this guide.Continue Reading

• 8 benefits of using big data for businesses

  Big data is a great resource for driving smart business decisions and changes. Here are eight ways that the use of big data is improving how business gets done.Continue Reading

• Customer segmentation analytics evolve with GenAI, ML

  GenAI, machine learning and advanced analytics techniques automate time-consuming aspects of customer segmentation, freeing up analysts to find insights and create value.Continue Reading

• 18 data science tools to consider using in 2024

  Numerous tools are available for data science applications. Read about 18, including their features, capabilities and uses, to see if they fit your analytics needs.Continue Reading

• 6 top predictive analytics tools for 2024

  Predictive analytics tools are evolving. Enhanced with AI, easier to use and geared to both data scientists and business users, they're more business-critical than ever.Continue Reading

• Advanced analytics challenges limit analytics, AI benefits

  Traditional advanced analytics are not going to disappear with the rise of generative AI. Cultural and quality challenges hinder organizations as attention shifts to new trends.Continue Reading

• 5 benefits cloud BI has over on-premises options

  BI moving from on premises to the cloud taps into operational improvements and benefits. Optimizing these tools creates a more customized, user-friendly experience.Continue Reading

• Clear the confusion of advanced vs. predictive analytics

  Advanced and predictive analytics are sometimes used as interchangeable terms. Users need to understand the differences of advanced analytics techniques to maximize insights.Continue Reading

• 8 ways to drive business value with advanced analytics

  It can be difficult to get buy-in for analytical operations. These eight bottom-line benefits of data analytics -- with real-world examples -- can win over execs.Continue Reading

• QlikWorld 2023 recap: The future is bright for Qlik

  Qlik celebrated analytics advancements at QlikWorld 2023, highlighting its acquisition of Talend, the evolution of Qlik Cloud, efforts to build data trust and more.Continue Reading

• Construct an event-driven architecture for real-time operations

  Event-driven architecture is one tool to tap into the potential of real-time analytics. Organizations should understand the structure and challenges of EDA to get started.Continue Reading

• 10 tools to level up streaming analytics platforms

  Streaming analytics platforms take real-time data and generate insight and value for organizations. Choosing the right tool from these options will help unlock benefits.Continue Reading

• Simulation and predictive analytics boost forecast capabilities

  Simulation and prediction analytics cover two different ways to forecast data. Together, they can boost capabilities, but organizations must craft them carefully to trust the results.Continue Reading

• What makes up an analytics pipeline?

  Analytics pipelines were traditionally hidden away, but they're changing as more organizations focus on agility for their data. Learn what makes up a successful analytics pipeline.Continue Reading

• Top 4 self-service BI benefits for organizations

  Self-service BI tools benefit organizations in four major ways, including improved decision-making, organizational efficiency, increased collaboration and reduced costs.Continue Reading

• The importance of continued business analytics education

  Business professionals can expand career opportunities by engaging in educational resources for business analytics, a key driver of data-driven decision-making and business success.Continue Reading

• How to evaluate and select data visualization tools

  Communicating data findings requires clear and informative visuals. Selecting the right tool starts with knowing the criteria to evaluate data visualization tools.Continue Reading

• Traditional BI vs. self-service BI shouldn't be a choice

  Traditional BI vs. self-service BI isn't a choice organizations need to make, but rather a partnership that requires elements from both to bring effective data use to users.Continue Reading

• 7 benefits of BI dashboards for businesses

  To reap the full benefits of BI dashboards, they need to be designed to empower end users and improve the efficiency of BI software and the decision-making process.Continue Reading

• What is predictive analytics? An enterprise guide

  Predictive analytics is a form of advanced analytics that uses current and historical data to forecast activity, behavior and trends.Continue Reading

• The benefits of embedded analytics

  The top business benefits of embedded analytics and BI include improving sales, gaining competitive advantages and getting maximum value from data to improve performance.Continue Reading

• Benefits of predictive analytics for businesses

  Predictive analytics' ability to forecast the future based on patterns in past data can give businesses a huge edge. Read about how to use this advanced form of business analytics.Continue Reading

• Descriptive vs. prescriptive vs. predictive analytics explained

  Analytics provides insight into the data today's businesses run on. Learn about the three main modes -- descriptive, prescriptive and predictive analytics -- and two variants.Continue Reading

• The business benefits of automating and embedding BI

  Automated insights and embedded BI are getting decision-makers the data needed to make quick decisions, accelerate business processes and lessen manual work required.Continue Reading

• 7 top predictive analytics use cases: Enterprise examples

  Across industries, companies are using predictive analytics to forecast future trends and actions. Learn about the most popular use cases for predictive analytics in 2022.Continue Reading

• Data science vs. machine learning vs. AI: How they work together

  Data science, machine learning and AI are central to analytics and other enterprise uses. Here's what each involves and how combining them benefits organizations.Continue Reading

• 8 top data science applications and use cases for businesses

  Data scientists engage in various applications to analyze data and create technologies. These are eight common ones, with examples from different organizations and industries.Continue Reading

• How to structure and manage a data science team

  Data science teams typically include various analytics and data professionals and can be set up in different ways, as explained here along with tips on managing them.Continue Reading

• 14 most in-demand data science skills you need to succeed

  The demand for data scientists continues to grow, but the job requires a combination of technical and soft skills. Here are 14 key skills for effective data scientists.Continue Reading

• Quiz: Big data analytics technologies and techniques

  Big data analytics technologies and techniques can help you gain valuable business insights. Take this quiz to test your knowledge of big data analytics tools and best practices.Continue Reading

• Does hiring a freelance data scientist make sense for you?

  Enterprises need to make the right hiring choices when it comes to supporting their data projects. Here are some reasons your company may or may not consider hiring a freelancer.Continue Reading

• Tips to prep for a data science interview

  Interviewing is an important first step toward a data science job. Here's advice for what questions to expect and how a little research can help with the technical screening.Continue Reading

• Data scientist job outlook in post-pandemic world

  There was a lull in hiring for one of the hottest jobs in the U.S., but as lockdowns start to lift and offices start to reopen, the data scientist job outlook is changing.Continue Reading

• What does NLP mean for augmented analytics?

  Explore how NLP is being used by augmented analytics platforms to improve employees' search capabilities, expand data visualization and build a data-driven culture.Continue Reading

• 8 big data use cases for businesses and industry examples

  As the understanding of big data requirements increases, so do big data use cases. Here are eight ways businesses are using big data to improve operations.Continue Reading

• Big data vs. machine learning: How they differ and relate

  Big data and machine learning are a powerful analytics pairing. Here's an explanation of the difference between them and how they can be used together.Continue Reading

• 6 reasons you may need data science as a service

  There are plenty of reasons to outsource all or part of a data science project to a service. Find out how enterprises are using DSaaS in their analytics pipeline.Continue Reading

• The top 4 self-service BI benefits for enterprises

  Self-service BI adoption is trending because it democratizes data access and analytics. Explore the benefits these platforms offer enterprises.Continue Reading

• What analytics leaders need to know about graph technology

  Enterprise graph analytics adoption has been trending recently and is only expected to grow. Gartner analyst Mark Beyer explores what you need to know about graph technology.Continue Reading

• Collaborative analytics benefits enterprise data analysis

  Sometimes, having more eyes on a problem can help solve it a little bit faster. Experts talk about the enterprise benefits of implementing collaborative analytics.Continue Reading

• What do you know about graph data analytics?

  Graph database and analytics adoption has been trending in the last few years as their use cases continue to expand. Use this quiz to find out what you know about the technology.Continue Reading

• Ultimate guide to business intelligence in the enterprise

  Enterprise BI systems bring a variety of uses, business benefits and challenges to organizations, as explained in this in-depth business intelligence guide.Continue Reading

• Top tips for a successful self-service BI strategy

  As self-service BI adoption continues across enterprises, it's important to make sure you have a good strategy. Here are the top tips for a successful self-service deployment.Continue Reading

• Top 5 enterprise graph analytics use cases

  Gartner expects enterprise graph analytics adoption to grow in the coming years. Read on to find out why the technology is on the rise across organizational markets.Continue Reading

• Python code formatting: Tools you need and why it matters

  Computers don't care about the style of your code, so why should you? See what Al Sweigart has to say about code formatting, and get a sneak peek at his new book.Continue Reading

• Do you need a data warehouse for business intelligence?

  Some organizations have moved away from using data warehouses in their business intelligence strategies. Read on to find out how approaches to data storage for BI are changing.Continue Reading

• Decision intelligence software boosted by analytics, AI

  Enterprise adoption of decision intelligence is projected to grow in the next few years. Find out how analytics and AI support decision modeling and how organizations are using it.Continue Reading

• Automotive analytics drives consumer-focused industry

  The automotive industry and analytics have always worked in tandem, and now with a shift in focus from product to consumer prompted by market changes and economic downturn.Continue Reading

• Why using graph analytics for big data is on the rise

  Graph analytics is being used across industries for different reasons. Read on to see how they can improve organizational decision-making, network analysis, production and more.Continue Reading

• 6 top business benefits of real-time data analytics

  The potential benefits of real-time analytics applications for organizations include faster decision-making, increased business agility, better customer service and more.Continue Reading

• Augmented analytics lead analytics trends for 2021

  Augmented analytics adoption was one of the top trends for 2020. Adoption still seems strong for 2021 as well as personalization the role of AI in analytics overall.Continue Reading

• Analytics in real estate thrive in the commercial market

  Data can drive everything from investment to redevelopment in the commercial real estate spaces, and analytics will continue to lead change in the industry.Continue Reading

• 15 common data science techniques to know and use

  Data scientists use a variety of statistical and analytical techniques to analyze data sets. Here are 15 popular classification, regression and clustering methods.Continue Reading

• Event streaming technologies a remedy for big data's onslaught

  Event streaming is emerging as a viable method to quickly analyze in real time the torrents of information pouring into collection systems from multiple data sources.Continue Reading

• Brain teasers and other fun tips for learning Python

  Learn about some interesting ways Python coders can grow their skills in the language and the importance of connecting and learning from others in the community.Continue Reading

• Why ethical use of data is so important to enterprises

  With everything else going on this year, data privacy has been front of mind for many consumers, accompanied by ethics related to how their data is collected and used.Continue Reading

• How DataOps architecture benefits your analytics strategy

  A DataOps framework can provide access more efficiently throughout an organization to ease the analytics process and deliver insights faster.Continue Reading

• Chief data and analytics officer roles: What you need to know

  Whether you have a chief analytics officer or chief data officer, there is a need for a unified leadership structure for data and analytics in the enterprise.Continue Reading

• Enterprise analytics benefits of natural language processing

  As more analytics vendors adopt natural language tools, enterprises may want to think about the benefit the technology provides to their analytics abilities.Continue Reading

• Emotions analytics helps Hotels.com connect with customers

  While traveling has been halted for most of us, marketing efforts in hospitality still go on, and one way to sharpen those efforts is building an emotional connection -- with data.Continue Reading

• Certificates important to the data science learning path

  While data science certificates have value in the professional world, candidates must make them a piece of a larger drive for technical mastery and continued education.Continue Reading

• The 5-step process for finding data science leader unicorns

  Companies continue to struggle to effectively hire for their data science teams, but Gaurav Anand says that a hybrid solution that considers tech and business knowledge might work.Continue Reading

• Comparing business intelligence vs. business analytics

  Business intelligence with descriptive analytics gives a better understanding of your current operations, while business analytics aims to inform future decisions.Continue Reading

• Using data for public good in fight for racial equity

  While some data-driven methods recently have been publicly scrutinized for biases in practice, there are plenty of ways data can aid the fight for racial equity.Continue Reading

• Why more employees need data literacy skills

  Encouraging employees to learn data literacy skills can benefit any enterprise. Read on for some of the benefits and resources to take advantage of in building those skills.Continue Reading

• 20 top BI tools and how to choose the right one

  To help you buy the right BI tool for your data analysis needs, here's a look at 20 leading technologies, the different types of BI software and key features to look for.Continue Reading

• Python exploratory data analysis and why it's important

  Exploratory data analysis is a key step to building the best models to gain insight from your data. Read on to see how Python can be a useful tool in this process.Continue Reading

• Ensuring predictive model accuracy in the age of COVID-19

  Data scientists are used to concept drift, but the constantly changing data due to COVID-19 can be hard to address. Experts discuss how to maintain model accuracy in the pandemic.Continue Reading

• Implementing an analytics business plan requires commitment

  To get the most out of a data analytics business plan, companies must have clear goals and communication, as well as proper buy-in companywide.Continue Reading

• State of the self-service analytics market

  Self-service analytics are important to strong enterprise analytics. Experts talk about how top vendors in the market are keeping up with user needs.Continue Reading

• Key elements of a DataOps framework for BI and analytics

  DataOps brings speed and agility to BI processes and helps align data management to business goals. Learn about the key elements of a DataOps framework.Continue Reading

• What does Salesforce mean for Tableau AI features?

  Tableau and Salesforce both offer AI features for their analytics tools. Experts talk about how the AI offerings from each platform can complement each other.Continue Reading

• 5 valuable business intelligence use cases for organizations

  BI tools and applications can help improve decision-making, strategic planning and other business functions. Here's a look at five top BI use cases for organizations.Continue Reading

• Benefits of embedded BI and customizable analytics

  Depending on your data needs, embedded analytics from a BI platform or a more custom-built analytics framework may work. Read on for the benefits of each option.Continue Reading

• Data scientist vs. machine learning engineer careers

  There are many careers under the data science umbrella, including data scientist and machine learning engineer. But what's the difference between the two? Read on to find out.Continue Reading

• How to choose self-service BI tools using analyst reports

  When deciding on what BI tools to use, many organizations turn to reports from analyst firms. Here's how to decipher the ratings to pick the right tools for your organization.Continue Reading

• The most important soft skills for data scientist jobs

  Soft skills are an important part of data scientist jobs. From business value to interpersonal communication, many nontechnical skills are important to data science projects.Continue Reading

• Key considerations for choosing embedded analytics tools

  Many organizations benefit from using embedded analytics tools. Here's a guide on some key things to consider before deciding on an embedded analytics vendor.Continue Reading

• Embedded BI and analytics apps speed workflows, insight access

  Embedded BI is fast becoming a focal point for analytics uses as data analysts, developers and business users enjoy faster processing, reduced workloads and better outcomes.Continue Reading

• What Salesforce means for Tableau in the cloud

  After the Salesforce acquisition, users have wondered about the future of Tableau in the cloud. Experts weigh in on how the transition could benefit the platform.Continue Reading

• Ethical data collection in the spotlight over new regulations

  New regulations have put data privacy top of mind for many consumers. Here's a look at how businesses can incorporate ethical data collection -- and even benefit from it.Continue Reading

• The data science pathway demands continued learning

  With the advent of open source coding languages and the expansion of online courses, the pathway to becoming a data scientist has never been easier.Continue Reading

• How to improve data scientist job satisfaction

  Hiring data scientists is tough. Keeping them is tougher. However, there are certain things companies can do to minimize the high cost of turnover within their data science team.Continue Reading

• How to compare and choose augmented analytics tools

  Choosing an augmented BI and analytics vendor can be difficult when their offerings are so similar. Analysts at Gartner and Forrester offer advice for choosing augmented analytics tools.Continue Reading

• 5 ways enterprises adapt to the data scientist shortage

  Where are all the data scientists? Coping with the data scientist shortage is a struggle for many enterprises. Here are five ways to effectively manage with the shortage.Continue Reading

• Augmented analytics tools: Business uses, benefits and barriers

  This guide examines the capabilities and potential benefits of augmented analytics technologies and offers guidance on how to use them to simplify BI and analytics processes.Continue Reading

• Automated tools broaden the future scope of data science

  Automated data science tools may make their way into the data science process, but are unlikely to ever be able to do everything human data scientists do, experts say.Continue Reading

• Everything you need to know about augmented analytics vendors

  Augmented analytics is set to become the newest trend in BI and analytics, and vendors are making big investments to develop products smarter for a wider range of users.Continue Reading

• Tableau or Qlik: What separates the data visualization tools?

  While leading data visualization vendors Tableau and Qlik may seem similar, there are substantial differences. Understanding the differences is key to making the right decision.Continue Reading

• Salesforce acquisition of Tableau likely to bring changes

  Since Salesforce's Tableau acquisition, many have wondered what will happen to Tableau's on-premises customers. Find out what industry experts have to say.Continue Reading

• NLP uses in BI and analytics speak softly but carry a big stick

  Self-service analytics vendors are adding NLP features to their tools to make them even easier to use. Learn about notable NLP applications as well as some caveats.Continue Reading

• NLP progress in BI and analytics slowed by language barriers

  Natural language processing shows potential in simplifying data access and deriving deeper insights, but NLP's strengths can be its weaknesses in reaching the Promised Land.Continue Reading

• Data science storytelling emerges as top analytics skill

  Storytelling in data science is emerging as a critical skill to have in analytics. Without it, data-driven insights have a tendency to wither on the vine.Continue Reading

• What's behind the Domo machine learning tool Did You Know

  Domo's Did You Know feature uses machine learning algorithms to automatically pull analytics information out of data sets for business users. Here's how it works.Continue Reading