Follow Datanami:

Tag: dataops

ClearML Announces General Availability for Enterprise

ClearML, a unified MLOps platform, has announced the general availability of ClearML for enterprise customers. The platform was previously offered as invite-only to a select group of customers but is now broadly avail Read more…

Unravel Data Aims to Straighten Out The Data Stack with $50M Series D

The enterprise data stack continues to grow in complexity with a sometimes overwhelming number of tools, systems, and data pipelines to manage and optimize. When you factor in the shift to the cloud, managing compute and Read more…

How DataOps Strengthens Business Resilience and Agility

Agility is critical for any business looking to grow and remain relevant in today’s complicated industry landscape. Being able to quickly respond and reliably deliver actionable insights is vital for businesses — esp Read more…

Why DataOps-Centered Engineering is the Future of Data

DataOps will soon become integral to data engineering, influencing the future of data. Many organizations today still struggle to harness data and analytics to gain actionable insights. By centering DataOps in their proc Read more…

Apache DolphinScheduler Raises Nearly $10M Angel Financing

DataOps platform Apache DolphinScheduler announced it has recently raised nearly $10 million in angel round financing. The Beijing-based company plans to use the funds for R&D in MLOps and data synchronization techno Read more…

Building Continuous Data Observability at the Infrastructure Layer

Data is the lifeblood of business today, but getting it where it needs to go is hard, especially as data volumes grow. Data pipelines become the repeatable method for moving this digital crude, but monitoring the flows f Read more…

Software AG to Acquire StreamSets

Veteran German enterprise software company Software AG — coming up on its 55th anniversary — is bringing another company into its fold: San Francisco-based StreamSets, which has been offering an enterprise-grade data Read more…

Leaky Pipelines and the Business Case for Data DevOps

As enterprises embrace digital transformation and migrate critical infrastructure and applications to the cloud as a key component of those efforts, what can be called “data clouds” have started to take shape. Built Read more…

Top Trends for Business Analytics for the Rest of 2021

Data powers business. Organizations rely on it to remain successful and competitive, but they have traditionally performed analysis on huge volumes of historical data to make critical decisions. The impact of the Covid-1 Read more…

In Search of the Modern Data Stack

The modern data stack is many things to many people. It’s multi-cloud! It’s the data mesh! It’s BI plus AI! To get a better visibility into just what the modern data stack is, how it’s evolving, and why it all ma Read more…

Why Every Enterprise Needs a Data Fabric & DataOps to Solve Their Data Management Woes

Sponsored Content by Hitachi Vantara

Enterprises today want to have real-time business insights into what’s happening to take actions that ultimately increase operational efficiencies, improve customer engagement, and grow revenue. However, the promise of Read more…

Hands-Off: Manual Data Integration Tasks Plummeting, Gartner Says

While the need to integrate data has never been greater, the addition of machine learning and other forms of automation is driving a large reduction in the amount of manual data management tasks that human workers are re Read more…

Master Data Management: Three Paths to Creating a Successful, Low-Risk Program

The biggest danger to a nascent master data management (MDM) program is starting with the wrong objectives, even though they can often sound quite right. While well-intentioned, unclear business objectives--such as creat Read more…

Bridging the Gaps in Edge Computing

Aside from the lure of the public clouds, which got bigger and stronger in 2020 amid the COVID-19 scourge, the world of data and analytics became a lot more distributed last year. While it seems clear that most AI models Read more…

In Search of Data Observability

The concept of “observability” is well understood as it pertains to DevOps and site reliability engineering (SRE). But what does it mean in the context of data? According to Barr Moses, the CEO of data observability Read more…

A ‘Glut’ of Innovation Spotted in Data Science and ML Platforms

These are heady days in data science and machine learning (DSML) according to Gartner, which identified a “glut” of innovation occurring in the market for DSML platforms. From established companies chasing AutoML or Read more…

Tackling Data Governance in a Multi-Cloud DW World

Microsoft Azure Synapse is the top destination for customers adopting cloud data warehouse over the next 12 to 24 months, followed by Databricks and Amazon Redshift, according to a new data engineering study released tod Read more…

Enabling DataOps for Analytics

Sponsored Content by Qlik

Modern enterprises need to quickly deliver the right data to a growing data consumer audience to drive strategic initiatives, often encompassing data science and machine learning, and thereby create competitive advantage Read more…

Running Sideline to Sideline with Big Data

What can you do with big data? A better question might be what can’t you do. From a big data point of view, we are living in extremely resource-rich times, with a huge assortment of tools, framework, and platforms to c Read more…

Zaloni Pivots to DataOps

Zaloni once was focused on helping customers to manage data in Hadoop. But under new CEO Susan Cook, the company has broadened its scope and is now aiming to help customers manage the entire supply chain of data, or what Read more…

Older Entries
Datanami