I first wrote about a new era of trade a few years ago to make the point that the period of optimizing supply chains for the lowest cost was over, and that companies needed to redesign them to achieve greater resiliency. That observation proved correct. Now we are hearing about “the end of globalization,” a hyperbolic phrase describing the effects of ongoing changes to the international political order that have been underway for more than a decade. These changes are forcing companies to make sometimes significant adjustments to sourcing and supply chain management. Globalization, which started in 1492, isn’t over, but managing international trade requires the ability to deal with shifts in strategic planning assumptions and agility in dealing with tactical events. Software will play an important role in enabling corporations to meet these ongoing challenges caused by a major reordering of global trade.
Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our Data Lake Dynamic Insights Research reported they were currently using data virtualization, and another two-quarters (46%) planned to include data virtualization in the future. Even more interesting, those who are using data virtualization reported higher rates of satisfaction (79%) with their data lake than those who are not (36%). Our Analytics and Data Benchmark Research shows more than one-third of organizations (37%) are using data virtualization in that context. Here, too, those using data virtualization reported higher levels of satisfaction (88%) than those that are not (66%).
I recently wrote about the importance of data pipelines and the role they play in transporting data between the stages of data processing and analytics. Healthy data pipelines are necessary to ensure data is integrated and processed in the sequence required to generate business intelligence. The concept of the data pipeline is nothing new of course, but it is becoming increasingly important as organizations adapt data management processes to be more data driven.
Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, Digital transformation, data lakes, AI and Machine Learning, data operations, Digital Business, data platforms, Analytics & Data, Streaming Data & Events
Data governance is an issue that impacts all organizations large and small, new and old, in every industry, and every region of the world. Data governance ensures that an organization’s data can be cataloged, trusted and protected, improving business processes to accelerate analytics initiatives and support compliance with regulatory requirements. Not all data governance initiatives will be driven by regulatory compliance; however, the risk of falling foul of privacy (and human rights) laws ensures that regulatory compliance influences data-processing requirements and all data governance projects. Multinational organizations must be cognizant of the wide variety of regional data security and privacy requirements, not least the European Union’s General Data Protection Regulation (GDPR). The GDPR became enforceable in 2018, protects the privacy of personal or professional data, and carries with it the threat of fines of up to 20 million euros ($22 million) or 4% of a company’s global revenue. Europe is not alone in regulating against the use of personally identifiable information (other similar regulations include The California Consumer Privacy Act) but Ventana Research’s Data Governance Benchmark Research illustrates that there are differing attitudes and approaches to data governance on either side of the Atlantic.
Although the bulk of contact center seats are still served by on-premises equipment, there appears to be a consensus that the cloud is better suited to delivering a successful, omnichannel customer experience, and that most new contact center deployments will be run on cloud-computing platforms.
I recently described the growing level of interest in data mesh which provides an organizational and cultural approach to data ownership, access and governance that facilitates distributed data processing. As I stated in my Analyst Perspective, data mesh is not a product that can be acquired or even a technical architecture that can be built. Adopting the data mesh approach is dependent on people and process change to overcome traditional reliance on centralized ownership of data and infrastructure and adapt to its principles of domain-oriented ownership, data as a product, self-serve data infrastructure and federated governance. Many organizations will need to make technological changes to facilitate adoption of data mesh, however. Starburst Data is associated with accelerating analysis of data in data lakes but is also one of several vendors aligning their products with data mesh.
How payments are effected is an afterthought to many involved in a transaction, but flaws in this process can be a source of pain and frustration for those in the back office, especially in accounting and treasury. To improve the way payments are handled in business-to-business transactions, the once ubiquitous paper checks are giving way to electronic payments. This category includes credit, debit and virtual cards, wire transfers, as well as ACH (Automated Clearing House) transmissions that may be in the form of direct deposits, direct debits and electronic checks. Electronic payments are supplanting checks because they lower processing costs for both parties in a transaction; increase accuracy, auditability and control of the accounting; provide better visibility into payment status; and enable deeper insight into spend or customer metrics. Building on these digital advances, blockchain payment systems (BPS), now at an early stage in development and adoption, have significant potential in the market because they offer similar advantages at an even lower cost. I assert that by 2025, fewer than 20% of organizations will be using blockchain payment systems, but those that do will speed transactions, reduce overhead and cut costs.