Resource Categories: Analyst Reports

Data-intensive applications help customers, employees, and other users do business and make the best decisions in various real-world contexts.

These applications—which embed sophisticated analytics and business logic that feed on fast-changing volumes and varieties of data—deliver guidance that can adapt in real time to user circumstances.

To tailor these applications for their intended uses, application providers require a robust development and operationalization workflow that accelerates and automates the sourcing and preparation of data, the building and training of analytics, and the management of assets (plus the necessary programming code) in cloud-based production environments.

This TDWI Checklist Report presents best practices for application providers to accelerate this workflow in the cloud. It addresses such imperatives as user journey alignment, scalable resource provisioning, rapid application deployment, unified pipeline workflows, comprehensive observability, and maximum application reusability.

Modern enterprises are expanding their analytics programs to improve their ability to make fact-based decisions, plan for an uncertain future, compete on analytics, and grow customer accounts. These high-value business goals require advanced forms of analytics, which in turn demand use-case-appropriate data integration, data platforms, and other data management. Without the right data in the right format on the right platform, critical and expensive
efforts in advanced analytics have little or no business value.

This report defines data management for advanced analytics (DM for AA), which tailors established and emerging data management best practices and techniques to specific forms of advanced analytics, thereby raising the precision, productivity, and business value of analytics.

This TDWI Best Practices Report explores data management strategies and best practices, then links combinations of these to the leading forms of advanced analytics to help data management and advanced analytics professionals and their business counterparts achieve greater success and business impact.

Data monetization opportunities are increasingly within reach of businesses everywhere. Recent innovations in converged data analytics platforms can accelerate an enterprise’s ability to productize their data and other assets, such as trained machine learning models.

This Best Practices Report examines whether enterprise democratization of data and analytics is making a contribution to increased revenues, cost reductions, process efficiencies, returns on investment, and other quantifiable aspects of financial performance.

Excellence in personalization is a competitive differentiator. Customer retention and loyalty—critical to higher margins and profitability—depend on personalization.

Customers enjoy having the power to select features and tailor products. Many are willing to pay higher prices for products they can customize. Organizations need timely, quality information to ensure that personalization options are appropriate for each customer.

Organizations have long used characteristics such as gender, household size, education, occupation, and income to segment customers for marketing. Smarter segmentation based on analytics, including artificial intelligence and machine learning (AI/ML), allows you to move beyond standard segmentation and one-size-fits-all marketing. Powered by data, you can develop micro-segments, explore data relationships across segments to tailor offerings, and move toward personalized, one-to-one marketing.

This TDWI Insight Accelerator focuses on data-driven personalization strategies for retail and consumer packaged goods (CPG) organizations. Many of the issues are also of interest to marketing functions in other industries.

What is the data economy? How can you leverage it? And, why care–what’s possible once you’re successful?

We conducted global research to find out. We learned that organizations exploiting near-boundless access to data, data services, business insights and data collaboration are solving some of the most complex business problems while also creating new market opportunities.

These Data Economy Leaders accelerate time to market for new products, best know and serve customers, and outthink bad actors to minimize fraud. Those pushing the boundaries of the data economy have built new revenue streams with data products and services made available to their customers, partners, and any other organization.

Data Economy Leaders outperform all others in revenue growth, customer satisfaction, market leadership, and other business metrics. Download the report to find out:

• What characterizes Data Economy Leaders (and those lagging behind)
• How your organization can become a leader and the business benefits that result
• Which industries are winning (or lagging) in the data economy and how
• What advice chief data officers (CDOs) from leading brands have for aspiring organizations
• What Snowflake recommends for how to get started and which efforts to prioritize

Maximizing the value of data platforms with data integration and data management capabilities is essential for organizations that want to become data- and analytics-driven. Increasingly—but not entirely—based in the cloud, these systems and services are the engine of modern applications and smarter processes for higher business efficiency and innovation.

Research indicates the need for tighter integration between two traditionally separate worlds: one devoted to analytics generation and the data integration, platforms, and management that support analytics, and the other devoted to mission-critical business applications and processes essential to operations across enterprises.

The American Rescue Plan Act of 2021 along with the Coronavirus Aid, Relief, and Economic Security (CARES) Act of 2020 have provided trillions of dollars in economic stimulus funding. Included in this legislation are billions of dollars through which state and local governments can modernize technology and provide improved services to citizens.

In partnership with Snowflake, the Government Business Council (GBC) interviewed Chief Data Officers (CDOs) from across the country in order to better understand how states are using this federal funding to modernize network systems, improve data sharing, and address unemployment fraud.

Download this report to learn:

• How states are leveraging stimulus funding for technology modernization
• How state CDOs work together to manage, protect, and share data
• How states are dealing with data silos and stimulus fraud

What is the data economy? How can you leverage it? And, why care–what’s possible once you’re successful? 

We conducted global research to find out. We learned that organizations exploiting near-boundless access to data, data services, business insights and data collaboration are solving some of the most complex business problems while also creating new market opportunities.

These Data Economy Leaders accelerate time to market for new products, best know and serve customers, and outthink bad actors to minimize fraud. Those pushing the boundaries of the data economy have built new revenue streams with data products and services made available to their customers, partners, and any other organization. 

Data Economy Leaders outperform all others in revenue growth, customer satisfaction, market leadership, and other business metrics. Download the report to find out:

• What characterizes Data Economy Leaders (and those lagging behind)
• How your organization can become a leader and the business benefits that result
• Which industries are winning (or lagging) in the data economy and how
• What advice chief data officers (CDOs) from leading brands have for aspiring organizations
• What Snowflake recommends for how to get started and which efforts to prioritize 

Effectively creating a 360-degree customer view to enable customer centricity is critically dependent on effective and trustworthy data integration.

Successful efforts by organizations, especially in the financial services industry, have effectively leveraged integrated customer data. However, a recent TDWI survey found that 60% of all respondents felt that their MDM solutions needed some amount of upgrade, while 75% of financial services respondents felt this way.

Download this report to understand:

• Ongoing challenges to attaining a single source of truth for customer data such as systemic complexity, increasing data volumes, and changing expectations
• Trends that are accelerating the motivation to adopt full-scale governed custom centricity in the financial services industry
• How to achieve a true 360-degree customer experience