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Data Warehouse Modernization and Analytics for the Digital Enterprise     
More and more, organizations want to base decisions on facts, have complete views of customers, manage operations by the numbers, predict and plan strategically, and compete on analytics. As a foundation for achieving these goals, organizations need a modern infrastructure for data warehousing and business analytics.
Faster BI for the Masses: How Search Can Make Analytics More Accessible     
Business intelligence is critical to getting answers from data, but for many users it is also a huge source of frustration. Since its beginning, the mission of BI has been to make it faster and easier to locate the right data, query it, and return meaningful answers for reporting and analysis. Newer data visualization and discovery tools have improved the user experience, and data warehouses and data lakes have added terabytes to the data within reach. Yet, it still can be a slow and difficult process to get to the most relevant data without help from technical experts. Users often have to wait for their answers and unless the technical experts also have a strong understanding of the business, the answers are usually inadequate—and the process starts all over again.
Improving Analytics and Reporting with Near-Real-Time Data Replication     
Quality data analytics requires more than consolidating data in a central location; it demands up-to-the-minute captures. Find out how you can replicate real-time changes from an Oracle database to a SQL Server for all your analytics needs, whether your data is on premises, remote or in the cloud.
Seven Ways to Improve the Customer Experience with BI and Analytics     
Download this white paper for an exploration of seven technology innovations that can empower businesses to optimize the customer experience in today’s multichannel world.
Four Worst Practices for Leveraging P&C Information When Core Systems Change     
Property and casualty insurers are investing heavily in core system upgrades and replacements to better support new products, meet customer expectations, and improve operations. Download this white paper to learn the four worst practices that should be avoided during core system upgrades.
Agile, Fast, and Flexible: Five BI and Data Management Strategies for Meeting New Business Challenges     
A signature quality of leading companies is their ability to generate data-driven insights quickly so that they can proactively shift strategies to take advantage of new opportunities. They use data to learn sooner how customer preferences are changing, how to adjust when markets are shifting, and how they can reduce inefficiencies in operations so that resources are deployed the right way.
Business Intelligence Journal | Vol. 21 No. 1     
If your enterprise isn’t always looking for better ways to do things, you won’t move or stay ahead. In this issue of the Business Intelligence Journal we look at companies and the moves they’re making, as well as moves you can make in your own environment.
Ten Mistakes to Avoid In Preparing for IoT Analytics     
  By Fern Halper and Asim Razvi The Internet of Things (IoT)—a network of connected devices that can send and receive data over the Internet—is a hot market topic. Although many companies are excited about the possibility of improving operational efficiencies and driving new business models with IoT, this Ten Mistakes to Avoid identifies important factors to consider when getting ready for IoT analytics projects.
Data Warehouse Modernization in the Age of Big Data Analytics     
Data warehouses (DWs) and requirements for them continue to evolve. DWs are more relevant than ever, as they support operationalized analytics, and wring business value from machine data and other new forms of big data. Hence, it’s important to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. Yet, user organizations struggle to stay educated about trends and take the right action to modernize their DW investments. Many users need to catch up by deploying a number of upgrades and extensions to their existing DW environments and by adopting modern development methods. Once caught up, they need a strategy for continuous modernization.
Top Six Worst Practices in Business Intelligence     
Want to know why business intelligence (BI) applications succeed and BI tools fail? This white paper presents the six worst practices in BI and analytics, and helps you avoid them. You ll learn from the experiences of BI experts and information specialists and avoid mistakes such as Worst Practice #1: "Buying What Analysts Want instead of Considering the Needs of Others." It s a great guide to help you think through how to use BI to enable a culture where everyone is empowered to make better decisions.

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