Search Results for: data management

The Future of Computing: Harnessing Molecules for Sustainable Data Management

In this contributed article, Erfane Arwani, founder and CEO of Biomemory, discusses how molecular computing (using molecules rather than traditional silicon chips for computational tasks) could be a critical component in revolutionizing data storage, despite the exponential growth of AI.

From complexity to clarity: Harnessing the power of AI/ML and risk-informed strategies to streamline clinical data management

In today’s fast-paced world, driven by demands for speed and efficiency, the field of clinical development has undergone a remarkable transformation. The way trials are being conducted has changed significantly with decentralized clinical trials (DCT) becoming mainstream and the collection of clinical data from wearables and other remote-monitoring devices becoming common practice. While these advances […]

New Study Reveals Data Management Is a Top Challenge in the AI Revolution  

According to a new global study conducted by S&P Global Market Intelligence and commissioned by WEKA, the adoption of artificial intelligence (AI) by enterprises and research organizations seeking to create new value propositions is accelerating, but data infrastructure and AI sustainability challenges present barriers to implementing it successfully at scale. These challenges have been exacerbated by the rapid onset of generative AI that has defined the evolution of the AI market in 2023.

Acceldata and its Data Observability Platform – Solving Big Data Management Challenges

In this video interview with Ashwin Rajeeva, co-founder and CTO of Acceldata, we talk about the company’s data observability platform – what “data observability” is all about and why it’s critically important in big data analytics and machine learning development environments.

Cloudera Continues Rapid Pace of Data Fabric and Data Lakehouse Innovation to Extend Data Management Leadership

Cloudera, the hybrid data company, announced new hybrid data capabilities that enable organizations to more efficiently move data, metadata, data workloads and data applications across clouds and on premises to optimize for performance, cost and security. Cloudera’s portable data services enable simple, low-risk data workload and data application movement for ultimate data lakehouse optionality.

CIOs Say Data Management is Critical for Successful AI Adoption in New Global Research Report

A new survey report by MIT Technology Review Insights highlights AI and data management as essential pillars to enterprise success, but found that the majority of survey respondents cited data mismanagement as a critical factor that could jeopardize their company’s future AI success. The report, “CIO vision 2025: Bridging the gap between BI and AI,” was conducted in May and June 2022 in association with Databricks, pioneer of the lakehouse architecture.

Report: New Data Management Models Are Essential To Operate In The Cloud

As organizations increasingly embrace cloud-first principles and the quantity and variety of their data exponentially increases, Capital One’s new Forrester study finds the vast majority of data management decision-makers are deeply concerned about controlling and forecasting data costs, leveraging data at scale, addressing data quality and consistency, and better protecting data.  

Benefits of Automation for Enterprise Data Management

In this article we’ll take a look at how’s and why’s that organizations from many industries are jumping on the automation for data management movement. It’s important that stakeholders understand how well automation performs repetitive data management responsibilities, what tasks still require a human in the loop, and how to evaluate data management automation capabilities.

With Chips Scarce, Now is the Time for a Data Management Redo

In this special guest feature, Nathan Wilson, Channel Marketing Manager at Redstor, outlines why the current chip shortage presents a great time to review your data management strategy. There are several key challenges to keep in mind when it comes to hardware-based data management and protection.

Looking Ahead | Observability Data Management Modernization

In this contributed article, Karen Pieper, VP of engineering at Era Software, discusses how organizations today use real-time data streams to keep up with evolving business requirements. Setting up data pipelines is easy. Handling the errors at each stage of the pipeline and not losing data is hard.