The need to balance data safety with new data initiatives, deliver business value, and change company culture around data tops this year’s list of data and analytics management challenges.
The data landscape continues to increase in size and complexity and is more distributed than ever before. According to a survey conducted by Unisphere Research, “Data Quality Challenges and Strategies for the 2020s,” for many data managers, cloud provides opportunities to offload many of the rote or onerous tasks associated with data management, provisioning, and even security. However, data quality and integrity must, by necessity, remain within the purview of enterprise customers.
The growth of data in the cloud has been significant, the survey showed. Just about every enterprise stores data in the cloud; for 46% of enterprises, this constitutes most data (50% or greater) now maintained in the cloud—up from 32% just 1 year ago.
AI hit the ground running this year with the introduction of OpenAI’s ChatGPT. Generative Pre-trained Transformer (GPT) is a large-scale natural language technology that uses deep learning to produce human-like text. It is built on top of OpenAI’s GPT-3.5 and GPT-4 families of large language models and has been fine-tuned using both supervised and reinforcement learning techniques. It can be used to answer complex questions, write various prose, and even assist in coding or creating malware.
Also according to PwC, 72% of business leads in the U.S. believe AI will be the business advantage of the future. AI, robotics, and other forms of smart automation have the potential to bring great economic benefits, contributing up to $15 trillion to global GDP by 2030 according to PwC analysis.
However, concerns about the implications of unethical AI abound. A MITRE-Harris Poll survey on AI trends found that most Americans express reservations about AI for high-value applications such as autonomous vehicles, accessing government benefits, or healthcare. Moreover, only 48% believe AI is safe and secure, and 78% are very or somewhat concerned that AI can be used for malicious intent.
Many believe companies and the government should invest in responsible AI rules and regulations, with 82% of Americans and 91% of tech experts supporting government regulation. Also according to the survey, 70% of Americans and 92% of tech experts agree that there is a need for more industry investment in AI assurance measures to protect the public.
While everyone wants fast access to all the data they need, it must be governed and protected against security threats such as ransomware and managed for compliance with data privacy laws and regulations. According to Cybersecurity Ventures, global cybercrime will reach $10.5 trillion annually by 2025.
Tackling this issue requires investment, and the report forecasts that cybersecurity revenues will reach $344 billion worldwide by 2030.
Because more workforces are distributed, the report predicts that this year, more companies will work to adopt zero-trust architectures while also securing distributed end points to contain attacks and protect the entire corporate network.
Most companies have legacy systems and applications they rely on that aren’t going anywhere. However, they must learn to play with the newer technologies to meet evolving business requirements and expectations.
An IDG survey revealed that more than one-third of respondents (39%) reported that infrastructure holds their organization back from innovation. Specifically, many are finding their infrastructures aren’t properly optimized to support digital dexterity—a culture of practices that empower employees to deliver stronger value faster from ongoing digital initiatives.
As-a-Service platforms seen as critical to modernization efforts include Network as a Service (53%), Infrastructure as a Service (52%), Hybrid Cloud as a Service (51%), and Security as a Service (50%). However, skills issues and lack of dexterity in current infrastructures hold back the efforts of IT managers to deliver value to the business.
To help bring new resources and innovation to light, each year, Database Trends and Applications magazine presents the DBTA 100, a list of forward-thinking companies seeking to expand what’s possible with data for their customers. Spanning the wide range of established legacy technologies from MultiValue to cutting-edge breakthroughs such as Web3, the DBTA 100 is a list of hardware, software, and service providers working to enable their customers’ data-driven future.