Manufacturing Data + AI Predictions 2024

Recent advances in generative AI are actively changing every major sector of the economy. Its potential impacts across the manufacturing industry will be far-reaching, from increasing operational efficiency and productivity to strengthening collaboration across the globe.

Download the report to learn about our most important predictions for the manufacturing industry in 2024:

  • Generative AI will overhaul how manufacturers work by driving efficiency, productivity and innovation
  • AI and data will inform critical business decisions across the value chain
  • A robust data foundation will distinguish leaders in manufacturing

Retail and Consumer Goods Data + AI Predictions 2024

Rapid developments in generative AI have already begun to affect the retail and consumer goods industry. While shoppers and the wider retail industry try to work out exactly what to think of these technologies, the businesses that move quickly to adopt generative AI and new data strategies into their operations will best position themselves for success.

Download the report to learn about our most important predictions for the retail and consumer packaged goods (CPG) industry in 2024:

  • Experimenting with generative AI will put retailers and consumer goods companies ahead of the curve on productivity.
  • Data monetization will play a massive role in driving revenue.
  • A strong data strategy will distinguish industry leaders from followers.

Harnessing the Power of Diverse Data for Business Growth

Today’s competitive business landscape demands comprehensive, data-driven insights. Enterprises are beginning to utilize diverse data—which includes structured, semistructured, and unstructured forms—to fuel these insights.
Diverse data is extremely important for enriching data sets for analysis as well as promoting innovation in companies. Yet, results from this research indicate that it is still relatively early days for making the most out of diverse data. Survey respondents are facing challenges, including unifying diverse data for analysis, securing the data, determining data quality guidelines for diverse data, and finding tools to help them analyze diverse data.
How are most companies dealing with diverse data? How are they sourcing it? How are they using it? Managing it? Analyzing it? How are they governing it? Can we learn anything from those with experience with diverse data? These topics are covered in this Best Practices Report.

Public Sector Data + AI Predictions 2024

In 2024, rapid developments in generative AI, coupled with changes in policy guidance and public sentiment, will likely compel governments to adopt new technologies more quickly than at any time in recent memory. In this report, our in-house experts weigh in on the impact of AI and other developments on the public sector. 

Read the report to learn key industry predictions for 2024, including:

  • How the public sector will embrace AI to solve long-term problems — eventually
  • Why agencies will accelerate cloud migration and adoption of data management platforms
  • Why governments will organize data marketplaces to grow GDP
  • And much more

Using Generative AI to Improve Operational Efficiency and Data-Driven Decision-Making

Generative artificial intelligence (AI) is poised to transform practically every type of work. The potential of generative AI lies in its ability to automate development of every type of knowledge-based output. In the process, generative AI can boost the operational efficiency of many business processes that traditionally have relied on manual human efforts, as well as augmenting the productivity of humans in many knowledge-intensive functions.

This TDWI Insight Accelerator focuses on current enterprise practices and key steps your organization can take to unlock the potential of generative AI.

The Forrester Wave™: Cloud Data Warehouses, Q2 2023

Cloud data warehouses help organizations modernize their analytical platform. Forrester researched and analyzed the most important providers in the space and named Snowflake one of the leaders.

Download your complimentary copy of the report to learn:

  • How easy Snowflake customers say the solution is to use
  • How highly automated Snowflake is, “requiring zero administration”
  • Why Snowflake is ahead of other vendors when it comes to innovation, including AI/ML

Snowflake in Healthcare 2023 Report

KLAS Research is an industry leader in analyzing IT solutions and services for healthcare organizations. KLAS recently evaluated Snowflake’s Healthcare & Life Sciences Data Cloud based on data integration, cloud capabilities, and performance across six customer experience pillars—culture, loyalty, operations, product, relationship and value.

Report highlights include:

  • Why the top customer outcomes are operational efficiency and cost-effectiveness
  • In-depth insights from Snowflake healthcare customers about their experience
  • Why Snowflake received a 92.2*% performance score
  • Customers’ long-term plans for using Snowflake

Download now.

*Some respondents chose not to answer particular questions. As a result, there was limited data available. This statement reflects the impact of non-responses on data availability.*

 

O’Reilly Report: Designing a Modern Application Data Stack

The pressure to deliver data-driven insights faster across diverse use cases is prompting product leaders to rethink their data application approach. Modern cloud-based data platforms provide the power and flexibility teams need to create highly scalable applications efficiently.

In this report, we explore the synergy between cloud data platforms and data-intensive applications, highlighting key considerations that help accelerate app development, deployment, and adoption.

You’ll learn:

  • Why modern cloud data platforms are a great fit for data applications
  • Considerations for building data apps at scale, including resource sharing, multi-tenancy, and workload isolation
  • Data processing best practices
  • Methods to modernize application distribution for providers and consumers

Six Best Practices for Harnessing Real-Time and Streaming Data Pipelines

As competitive pressures increase, many organiza­tions want to leverage higher volumes of diverse data for analytics and new appli­cations, including real-time and streaming data.

Streaming data refers to data that is gener­ated continuously in a stream, typically at high volume, either at regular or irregular intervals. Working with streaming data may involve capturing multiple streams for later analysis or processing, or analyzing one or more streams in real time—for example, to immediately capture data that deviates from the norm.

Successful applications of streaming data can improve operational processes and reduce costs by quickly identifying problems. They can help organizations improve the customer experience and provide new and innovative applications that can add to a company’s bottom line. Yet organizations face difficulties using their current data platforms, integration, and management to handle real-time data streaming.

This TDWI Checklist Report examines six important considerations and best practices for managing streaming data for real-time use.

Best Practices Report: Achieving Scalable, Agile, and Comprehensive Data Management and Data Governance

The data explosion continues to accelerate across distributed landscapes with data on premises and on multiple cloud data platforms. Organizations face challenges as well as tremendous potential for increasing the value of data assets, including through data monetization—potential that can go untapped without good data management and governance.

Data-driven business initiatives depend on scalable, agile, and comprehensive data management and governance. The latest applications embed sophisticated analytics using AI/ML capabilities that must be provisioned with continuous, integrated, curated data to deliver insights to all users. Flexibility is key to keeping pace with business demand and unanticipated events.

This TDWI Best Practices Report focuses on understanding current challenges and providing best practices insights for modernizing processes and deploying technologies to solve them.