Features

Features

• Top 7 data preparation challenges and how to overcome them

  Data preparation is a crucial but complex part of analytics applications. Don't let seven common challenges send your data prep processes off track.  Continue Reading

• 9 examples of business intelligence use cases for companies

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

• 6 data preparation best practices for analytics applications

  Analytics applications need clean data to produce actionable insights. Six data preparation best practices can turn your messy data into high-quality fuel for analytics operations.  Continue Reading

• What is a business intelligence analyst and what do they do?

  Business intelligence analysts are key members of BI teams. Here's a look at the job, the skills it requires, salary levels and how the role of a BI analyst is evolving.  Continue Reading

• Business intelligence reporting: What it is, how it works

  BI reporting presents data in various formats so employees can interpret and act on that information in a timely manner without relying on a data analyst. But challenges exist.  Continue Reading

• Big data analytics and business intelligence: A comparison

  BI and big data analytics support different types of analytics applications and using them in complementary ways enables a comprehensive data analysis strategy.  Continue Reading

• The future of business intelligence: 10 top trends in 2024

  Various trends are affecting the current state of BI initiatives and their future direction. Here are 10 key ones that corporate leaders and BI teams should be aware of.  Continue Reading

• AI in business intelligence: Uses, benefits and challenges

  AI tools are becoming a key part of BI systems, both to add new analytics capabilities and simplify tasks. Here's what you need to know about using AI in the BI process.  Continue Reading

• GenAI demands greater emphasis on data quality

  As GenAI explodes and enables enterprise decision-making at previously unseen speed and scale, accurate information to train models and applications becomes increasingly important.  Continue Reading

• 9 types of bias in data analysis and how to avoid them

  Analytics can exhibit biases that affect the bottom line or incite social outrage through discrimination. It's important to address those biases before problems arise.  Continue Reading

• Qlik meets user needs with realistic approach to generative AI

  With trusted data as a foundation, the longtime analytics and data integration vendor has been pragmatic in its creation of an environment that enables generative AI development.  Continue Reading

• Treating data as a product a method to grow analytics use

  Treating BI assets such as models and dashboards as commodities is an emerging trend as organizations continue to seek new ways of making analytics use more widespread.  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

• Infusion of generative AI into analytics a work in progress

  Many vendors have introduced tools that integrate LLM technology with their platforms, but most are still refining the tools to ensure their accuracy and security.  Continue Reading

• Business efficiency a place to start with generative AI

  Increased efficiency is one of the main benefits of large language models, so one of the easiest ways for enterprises to start using LLM technology is by targeting inefficiencies.  Continue Reading

• Generative AI hype evolving into reality in data, analytics

  Organizations are already beginning to apply the technology to their data operations, helping expand analytics use to more employees and boosting the efficiency of data experts.  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

• Modernizing talent one of the keys to analytics success

  Adding a chief data officer, hiring data engineers and implementing a data literacy program are crucial aspects of reaching a desired level of data maturity.  Continue Reading

• Accounting giant boosts efficiency with Alteryx automation

  Two years after starting a pilot program with the data and analytics vendor, the accounting firm has saved more than 100,000 work hours by automating repetitive tasks.  Continue Reading

• Automation, more security and governance next big BI trends

  As many data preparation and management tasks get automated, insight generation and action are the next likely targets for automation. Another key trend is more data governance.  Continue Reading

• Sound business process architecture requires key traits

  Business processes require a coherent enterprise-level architecture. In this excerpt from his new book, Roger Burlton identifies key traits business processes should share.  Continue Reading

• Experts lay out data illiteracy's dangers, propose remedies

  In this excerpt from their new book 'Data Literacy,' top data management experts Peter Aiken and Todd Harbour outline a new way to gauge data learnedness.  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

• Gartner: Data-driven decision-making never more important

  Organizations must take a concerted approach to most effectively take advantage of their data, Gartner analyst Gareth Herschel said during the advisory firm's virtual conference.  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

• Data governance framework key to analytics success

  Successful data-driven decision-making relies on good data at its core, and it's a strong governance plan that ensures the quality of an organization's data.  Continue Reading

• Data-driven storytelling opens analytics to all

  Data storytelling, because it interprets and explains data, extends business intelligence to business users and not just those trained in data analysis.  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

• Key differences of a data scientist vs. data engineer

  Data scientists and data engineers often work together, and sometimes the positions are treated as the same. Read on to find out what makes the roles different from each other.  Continue Reading

• How to enhance your data science storytelling

  How do you create substantive, compelling stories for business executives from cold, hard numerical data? Experts share their tips on how to improve your data storytelling skills.  Continue Reading

• 4 ways natural language querying in BI tools can benefit users

  Natural language queries help ease access to BI data and improve analytics insights. See how organizations are putting natural language querying techniques to work.  Continue Reading

• Businesses look for tech solutions to big data security issues

  The growing adoption of big data analytics applications is complicating data security challenges -- and creating a need for new security strategies.  Continue Reading

• Big data vendors should stop dissing data warehouse systems

  Wayne Eckerson examines the analytics roles of data warehouses and big data systems and says he's tired of data warehouse bashing by big data vendors.  Continue Reading

• Data collection practices spark debate on big data ethics, privacy

  The increasing emphasis on collecting and analyzing big data is driving a debate on whether tighter privacy rules are needed to protect customers.  Continue Reading

• Selecting the right SQL-on-Hadoop engine to access big data

  Rick van der Lans explains why it's important to evaluate the differences in the technologies that make it possible to access Hadoop data using SQL.  Continue Reading