Trends in Data Management 2022
In today’s data-driven digital economy, organizations are increasingly looking for competitive advantages through reporting, analytics, and operational efficiencies. While this has been true for many years, there is an increasing maturity in the Data Management space as more organizations look to focus on Data Governance, Data Quality, and Data Security to ensure a solid data foundation for these efforts.
This paper analyzes the latest thoughts, trends, and activities related to data management survey respondents from around the globe. Download
State of Data Quality 2022
Almost seven in ten enterprises—69% of those who responded to TDWI’s practitioner survey—report that they have begun their Data Quality Management maturity journeys, but have not yet achieved high maturity. Download the full report commissioned by our partner Ataccama for additional insights into the DQ management market, including:
- A summary of the current state of enterprise data quality management in 2022
- Common challenges organizations encounter when managing their data quality
- What’s required to establish and maintain a mature enterprise DQ management practice
- Key success factors for mature DQ management
- 10 strategic recommendations from TDWI analysts for data management professionals
Trends in Data Management 2020
The rise of the data-driven organization has been a growing trend over the past several years. However, with the number of issues plaguing 2020, including the COVID-19 crisis, organizations have tempered their plans for significant expansion, focusing on the core fundamentals of analytics, warehousing, and the associated architecture and governance that will help them gain a fuller understanding of their organization and the market in order to face the challenges ahead. Despite these setbacks, Data Management is in a solid and arguably growth position as organizations look towards data to help them navigate the uncertain markets in the future. Download
Trends in Data Management 2019
In today’s fast-paced business environment, more and more organizations are looking to become data-driven, and with this comes a renewed interest in Data Management. In such dynamic times, Data Management becomes increasingly important both in “offense” mode – while driving business success and growth – and in “defense” mode – while protecting organizations against risk. This paper details and analyzes the latest thoughts, trends, and activities related to data management survey respondents from around the globe. Download
Data Governance in the Age of Self-Service Data Analytics
The rise of the data-driven business and digital transformation has increased business demand for data-centric skills and there is an increasing gap in IT skills to meet this need. As a result, more business-centric staff are taking an active role in the management and strategic analysis of data. Finding the right balance of roles and responsibilities is key to success in building a data-driven organization. This whitepaper explores how data governance can facilitate the success of self-service data analytics initiatives. Download
Trends in Data Architecture
In today’s data-driven economy, the definition and scope of Data Architecture is
changing and evolving at a rapid pace. Data Architecture is as much a business decision as it is a technical one, as new business models and entirely new ways of working are driven by data and information. This report looks to demystify a number of the current trends, provide practical insights into today’s modern Data Architectures, and insights into what might be the best possible choices for your organization. Download
Emerging Trends in Metadata Management
The push to become a data-driven enterprise is a growing trend in the industry as more and more organizations see the value of data as a strategic asset. In order to effectively leverage this asset, data must be of high quality and clearly understood. As a result, metadata is more important than ever before, with more than 80% of survey respondents stating that Metadata is as important, if not more important, than in the past. Read this research paper to find out why.
Download
Why a Data Model is Important to the Business
A high-level data model conveys the core concepts and/or principles of an organization in a simple way, using concise descriptions. The advantage of developing the high-level model is that it facilitates arriving at common terminology and definitions of the concepts and principles that drive the organization. This whitepaper provides an overview of why a data model is important to the business. Download
Integrating Packaged Applications: The Business Value of Metadata for Data Governance
CRM and ERP systems contain some of the most valuable data assets in the organization around customers, sales, campaigns, accounts payable, and more. Achieving a comprehensive view of systems such as these, however, is a daunting task due to their size and the high degree of complexity required to execute their business processes. These two conflicting aspects are what often create frustration and challenges many organizations—while these systems contain some of the most valuable information, they are also the most difficult to decipher. Data Governance and Metadata Management can play a critical role in integrating these systems with other business-critical systems in the enterprise to achieve business value. Download
Getting Your CRM Data Right: The Law of 80-20
Data is the bedrock of any effective CRM initiative. Lack of data focus will undermine and potentially sabotage your best efforts to build and sustain effective CRM processes and supporting platforms. This whitepaper outlines a simple set of steps that will help to identify and tackle the most important CRM data quality problems. Download
Trends in Data Management 2021
Digital transformation and the rise of the data-driven organization continue to drive Data Management across the globe. Increases in remote work and digital commerce, in part due to COVID-19 lockdowns, have only intensified these trends. Data stands at the center of digital transformation, and many organizations are focusing on Data Strategy to support opportunities through data while at the same time keeping data safe through Data Governance and Data Security. Survey participants focused on Data Architecture and Metadata Management technologies, and methods to fuel Data Management goals. Download
Trends in Data Management 2020
The rise of the data-driven organization has been a growing trend over the past several years. However, with the number of issues plaguing 2020, including the COVID-19 crisis, organizations have tempered their plans for significant expansion, focusing on the core fundamentals of analytics, warehousing, and the associated architecture and governance that will help them gain a fuller understanding of their organization and the market in order to face the challenges ahead. Despite these setbacks, Data Management is in a solid and arguably growth position as organizations look towards data to help them navigate the uncertain markets in the future. Download
Trends in Data Management 2019
In today’s fast-paced business environment, more and more organizations are looking to become data-driven, and with this comes a renewed interest in Data Management. In such dynamic times, Data Management becomes increasingly important both in “offense” mode – while driving business success and growth – and in “defense” mode – while protecting organizations against risk. This paper details and analyzes the latest thoughts, trends, and activities related to data management survey respondents from around the globe. Download
Data Governance in the Age of Self-Service Data Analytics
The rise of the data-driven business and digital transformation has increased business demand for data-centric skills and there is an increasing gap in IT skills to meet this need. As a result, more business-centric staff are taking an active role in the management and strategic analysis of data. Finding the right balance of roles and responsibilities is key to success in building a data-driven organization. This whitepaper explores how data governance can facilitate the success of self-service data analytics initiatives. Download
Trends in Data Architecture
In today’s data-driven economy, the definition and scope of Data Architecture is
changing and evolving at a rapid pace. Data Architecture is as much a business decision as it is a technical one, as new business models and entirely new ways of working are driven by data and information. This report looks to demystify a number of the current trends, provide practical insights into today’s modern Data Architectures, and insights into what might be the best possible choices for your organization. Download
Emerging Trends in Metadata Management
The push to become a data-driven enterprise is a growing trend in the industry as more and more organizations see the value of data as a strategic asset. In order to effectively leverage this asset, data must be of high quality and clearly understood. As a result, metadata is more important than ever before, with more than 80% of survey respondents stating that Metadata is as important, if not more important, than in the past. Read this research paper to find out why.
Download
Why a Data Model is Important to the Business
A high-level data model conveys the core concepts and/or principles of an organization in a simple way, using concise descriptions. The advantage of developing the high-level model is that it facilitates arriving at common terminology and definitions of the concepts and principles that drive the organization. This whitepaper provides an overview of why a data model is important to the business. Download
Integrating Packaged Applications: The Business Value of Metadata for Data Governance
CRM and ERP systems contain some of the most valuable data assets in the organization around customers, sales, campaigns, accounts payable, and more. Achieving a comprehensive view of systems such as these, however, is a daunting task due to their size and the high degree of complexity required to execute their business processes. These two conflicting aspects are what often create frustration and challenges many organizations—while these systems contain some of the most valuable information, they are also the most difficult to decipher. Data Governance and Metadata Management can play a critical role in integrating these systems with other business-critical systems in the enterprise to achieve business value. Download
Getting Your CRM Data Right: The Law of 80-20
Data is the bedrock of any effective CRM initiative. Lack of data focus will undermine and potentially sabotage your best efforts to build and sustain effective CRM processes and supporting platforms. This whitepaper outlines a simple set of steps that will help to identify and tackle the most important CRM data quality problems. Download