Data.
Not opinion.

Why Data Leaders Need to Care About Active Data Architecture™

Data architectures and their supporting technologies and capabilities (including analytic data infrastructure, and data engineering and data catalog products) face increased technology and business pressure to meet the requirements of more complex, diverse, and distributed business intelligence (BI) and analytics use cases and applications. The scale, distribution, mission-criticality, and pace of change facing data leaders and their teams is outpacing the ability of current architectural approaches. Data architectures that lack flexibility, adaptability, and scalability lead to challenges as organizations struggle to capture benefits and achieve positive returns from their BI investments.

In the face of these challenges, although data leaders realize they need to modernize data architectures to better support BI and analytics needs, they are unclear on how to do so in a game-changing manner. Approaches that continue to emphasize centralization, consolidation, physical data movement, and use-case-specific optimization remain common. Although better extract, transform, and load (ETL) processes and data-warehouse enhancements may yield marginal value gains, they will not create the breakthroughs needed to support the BI needs of the modern, Hyper-Decisive® organization.

2024-04-11

Criticality of MDM to Data Leadership

Master data management (MDM) represents a perennial issue for many organizations that want to establish and maintain a common frame of reference (some use the phrase “single source of truth”) within key organizational data and analytics. For many and for too long, many business leaders view MDM as an “IT thing,” allowing and enabling pursuit of master data objectives in the absence of explicit connection to business value chains and business processes.

In all instances, achieving high quality, high confidence, and ultimately high trust in the most critical data for organizations—customers, products, vendors, charts of account, and similar—is foundational. Master data domains are the “nouns” around which business value chains are organized.

2024-04-04

Dresner Advisory’s 5th Annual Business Intelligence Value Index®: Focus on Revenue to Deliver More Business Value From BI

2023 was a good year for growing revenue through the application of business intelligence (BI). Initiatives focused on revenue generation, compared to those focused on reducing costs, showed three times better results.

Consequently, the Dresner Advisory Services BI Value Index® rose to 10 percent in 2023, reversing a three-year downtrend. Most of the increase in the index came from a significant increase in organizations reporting the highest level of return on investment (ROI) from BI.

Organizations also tend to attach roughly equal importance to using BI to increase revenue or reduce costs. However, achievement data show that in 2023 organizations did a better job increasing revenue than cutting costs.

2024-03-29

Active Data Architecture Report 2024

The 2024 Active Data Architecture Market Study explores market requirements and priorities for data orchestration, integration, and transformations in the active data architecture pipeline workflow.

Active Data Architecture™ supports a platform-independent layer that sits between physical data stores and points of data consumption. It is comprised of various data management capabilities including virtualized and distributed data access (e.g., mesh, fabric), data governance, and security. At its core, Active Data Architecture is an abstraction layer translating business and physical structures. It is an architecture dynamically optimized for performance, scalability, and cost management.

Users in both information technology (IT) and business expect current data architectures and the supporting technology capabilities to meet the requirements of ever more complex, diverse, and distributed BI and analytics use cases and applications.

2024-04-11

2024 Cloud Computing and Business Intelligence Market Study

Cloud business intelligence is the technologies, tools, and solutions that employ one or more cloud deployment models.

We started tracking and analyzing this market dynamic in 2012 when adoption was nascent and with few organizations willing to invest. Now with 13 years of data, it is exciting to see the changes that have occurred since the early days of cloud-based solutions. Since that time, cloud-based, and especially public cloud-based solutions, have become increasingly dominant.

2024-03-25

Supply Chain Planning and Analysis Market Study 2024

Supply chain planning is the process of planning a product, sourcing raw materials, making products, through delivering those products to customers (other businesses and/or consumers), with the ultimate goal of balancing supply and demand. Supply chain analytics enables organizations to develop valuable insights associated with the procurement, processing, and distribution of goods. This is a key ingredient of overall supply chain management (SCM).

In this second edition of the Supply Chain Planning and Analysis Market Study report, we underscore the expanding role of performance management across various business functions beyond the traditional scope of finance. Facing an array of external challenges in the upcoming year, a more holistic approach to performance management is essential for organizations to respond adaptively, make informed decisions, and execute strategies with precision.

0024-03-15