APMdigest asked experts from across the IT industry — from analysts and consultants to users and the top vendors — for their opinions on the essential tools to support digital transformation. Part 5 is all about data.
CONTENT MANAGEMENT AND RECORD MANAGEMENT
Digital transformation presents opportunities to rethink and reinvent workflows, business processes, and customer service. Enterprise content management and records management provides instantaneous digital access to relevant information, with minimal effort. From a records management standpoint, built-for-purpose content services apps allows to integrate and manage information from previously isolated processes and silos –— meaning policies can now be applied to a much larger content pool. Policy application can now be automated, metadata and classifications are determined in the background, based on rules specific to the business process. Productivity and satisfaction increase as all this interconnected and analyzed content can now be surfaced in the right context across an organization's value chains and citizen-facing services.
Senior Director, Enterprise Product Marketing, OpenText
Digital transformation is a vague phrase with an unclear definition. One thing that is clear is the competitive value of being able to process and analyze the vast amount of data being generated by modern systems in a timely and effective manner. One must-have tool for harnessing this data is a fast and general engine for large-scale data processing. This tool provides high performance access to these dynamic but complex data collections, and provides interactive functionality which enables you to make better decisions more quickly and with a higher degree of confidence.
Manager, Community and Open Source Programs, Datadog
The crux of Digital Transformation is to obtain competitive advantage or improve efficiencies through actionable analytics. Thanks to on-demand access to powerful, scalable technologies, the cloud is ideally suited to consolidate data sets for high performance, integrated analytics. With efficient, continuous integration of high volumes of data between numerous sources and targets such as cloud infrastructures and increasingly ubiquitous data lakes, real-time data integration technology is the key enabler for Digital Transformation. The efficient and secure movement of data between sources and targets will allow organizations to derive more value from their data.
Mark Van de Wiel
The tool that is able to search, enrich and create useful information out of the petabytes of data that is being generated is the most important tool for digital transformation.You need to make sure you can measure what your users are doing but also be able to monitor and improve your infrastructure. Everything from the hardware to the software and the user needs to stored and correlated to make sure you can make the right decision.
Online Performance Consultant and Founder of Blue Factory Internet
CLOUD DATA MANAGEMENT
An organization that is truly committed to digital transformation must face the reality that a traditional on-premises data center is very often not the best venue for many types of digital initiatives. Digital transformation, therefore, inevitably leads to federated operations and infrastructure. Tools that enable the management of data and operations in a cross-cloud, multi-cloud environment are essential to long-term success in digital transformation.
CTO, JetStream Software
We see data storage as being the most crucial in digital transformation. Clearly, the most appropriate data storage solution evolves over the stages of the data life cycle. Not all stages are equal between the ingest or creation to the obsolescence and deletion of the data. Most critical is the active storage phase when the storage solution needs to deliver high performance to serve end-users in real time, be scalable to grow with expanding data sizes, reliable so it overcomes temporary hardware deficiencies and most importantly, cost effective.
CEO, Rozo Systems
FOCUS ON DATA
The most important factor to successful digital transformation is not a tool or technology, it's a mindset: an openness to putting data at the center of strategy and discovering the technologies best suited to transforming the business. Digital transformation must center around a data-driven opportunity. When companies force digital transformation, they often rush changes to one (or two) of three key factors: people, processes or technology. Therein lies the risk: change without sufficient focus on the data can cause a ripple effect of roadblocks and silos. A data-centric approach brings together the right people, practices and technologies –— such as analytics tools, AI and machine learning platforms, distributed application models, and in particular new data protection and management approaches –— to swiftly and safely dig out valuable insights from multiple data types and sources. In the coming years, new edge, core and cloud architectures will lead to data being even more distributed and dynamic than today. Digital transformation that's data-driven will enable real-time analysis at the edge and ensure the right data is being retained and protected for later decision making.
SVP and CTO, NetApp
Read The Essential Tools to Support Digital Transformation - Part 6, covering the development process.
A recent report by Workspot, State of End-User Computing and Remote Work highlights the consequences of the shift to remote and hybrid workstyles and how IT leaders are responding ... The report provides insights into three key areas and highlights the steps IT leaders are taking to mitigate risk and future proof their business ...
Forced by the pandemic to provide employees with access to the systems and information they needed to work from home, IT organizations around the world turned to traditional technologies like Virtual Private Networks (VPN). And they worked. But as the world moves to hybrid work, 96% of IT leaders who participated in a recent global survey conducted by Gartner Peer Insights on behalf of Citrix Systems, Inc., say they no longer cut it. And they're rethinking their approach ...
Artificial Intelligence for IT Operations (or AIOps for short) continues to be a hot topic among developers, SREs, or DevOps professionals. The case for AIOps is especially crucial given the expansive nature of today's observability efforts across hybrid and multi-cloud environments. As with most observability challenges, AIOps starts with telemetry data: metrics, logs, traces, and events ...
The development of the Thousand Brains Theory of Intelligence framework will now serve as a foundation for further research and new developments in Artificial Intelligence (AI) and Machine Learning (ML) ...
IT teams feel overwhelmed by too many tools that do not provide a unified view of the entire IT infrastructure, according to The Shift to Unified Observability: Reasons, Requirements, and Returns, a new independent survey conducted by IDC in collaboration with Riverbed ...
Legacy systems require a great deal of a prior knowledge, and then significant configuration, for anomaly detection to work effectively. ML and AI are beginning to change that, but it's important to really validate the claims of any NPM solution ...
Successful insight into the performance of a company's networks starts with effective network performance management (NPM) tools. However, with the plethora of options it can be overwhelming for IT teams to choose the right one. Here are 10 essential questions to ask before selecting an NPM tool ...
Hybrid and remote work environments have been growing significantly in the past few years. As individuals move away from traditional office settings in today's new remote and hybrid environments, many operational issues such as poor visibility into asset status and refreshes, unaccounted assets, and overspending on software are becoming a bigger challenge for IT departments ...
MLOps or Machine Learning Operations are a combination of best processes and practices that businesses use to run AI successfully ... While it is a relatively new field, MLOps is a collective effort that captured the interest of data scientists, DevOps engineers, AI enthusiasts, and IT ...
The data is in: enterprises are not happy with their managed service providers (MSPs) and cloud service providers (CSPs). According to the latest CloudBolt Industry Insights report, Filling the Gap: Service Providers' Increasingly Important Role in Multi-Cloud Success, 80% are so unsatisfied with their existing MSP and/or CSP, they are actively looking to replace them within 12 months ...