DataOps

Recently, ChatGPT has gained popularity, sparking a wave of enthusiasm for large-scale model products. As a result, major companies have been introducing or planning to launch their own large-scale model products. As someone who witnessed the previous AI wave, I have been thrilled because I have always hoped that AI could intelligently handle complex data governance tasks, freeing data professionals from cumbersome data operations. DataOps is an agile data management methodology that accelerates the entire data…

Before DevOps took the software engineering world by storm, developers were left in the dark once their applications were up and running.  Instead of being the first to know when outages occurred, engineers would only find out when customers or stakeholders complained of “laggy websites” or one too many 503 pages.  Unfortunately, this led to the same mistakes occurring repeatedly as developers lacked insight into application performance and didn’t know where to start looking to debug their code if something failed. The…

The article enlists the top 10 DataOps programming languages for developers to master in 2023 DataOps is a set of practices, processes, and technologies that combines an integrated and process-oriented perspective on data with automation and methods from agile software engineering to improve quality, speed, and collaboration and encourage a culture of continuous improvement in the area of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data…

The article lists the top 10 Dataops tools to master for a high-paying job in 2023  Nowadays businesses are data-driven. The art to gather data, analyzing it, and making decisions based on the analyzed data has always been a key part of success for any enterprise. As such, the ability to effectively manage data has become critical because of its explosion in size and complexity. It has made it difficult for businesses to promptly gather, analyze, and act on data. However, Dataops (data operations) is a software…

A virtual event gathering 2,000 data scientists, engineers and machine learning professionals to explore the intersection of machine learning data operations and AI India | October 27, 2022 — iMerit, a leading AI data solutions company, announced the second annual iMerit ML DataOps Summit, in partnership with TechCrunch, a virtual event focused on the intersection of machine learning data operations and artificial intelligence. The iMerit ML DataOps Summit is a live virtual event taking place on November 8 in the…

Have we found a fix for today’s data chaos and collaboration challenges?Photo by Chris Liverani on UnsplashData is getting even bigger, and traditional data management just doesn’t work. DataOps is on the rise, promising to tame today’s chaos and context challenges.Let’s face it — traditional data management doesn’t work. Today, 75% of executives don’t trust their own data, and only 27% of data projects are successful. Those are dismal numbers in what has been called the “golden age of data”.As data just keeps growing in…

ML model inferences as a new Data SourcePic Credit: Exploring the Unknown by Soma Biswas (Flickr: link, Reposted with Permission)As a Data Analytics & AI/ML practitioner, I still see a big disconnect between the two ecosystems.The first time I heard about DataOps and MLOps — the two frameworks enabling Data and ML pipelines, I was left wondering as to why do we need two separate frameworks? Data is a key ingredient of AL/ML (at least for supervised ML, which probably accounts for 80% of Enterprise AI today),…

DataOps jobs are in high demand from DataOps engineers to be well placed in the data-centric market Data science offers a wide range of data engineering jobs and DataOps jobs across the world in the data-centric market. DataOps vacancies are opening in all tech and data-related companies that need effective database management in 2022 and beyond. DataOps jobs include multiple roles including a DataOps engineer to build data products and engineer the production department with database management. The global…

Generally, data-driven companies mainly struggle with data quality issues. Massive amounts of data, changing data storage requirements due to changing company regulations, and the various types of data sources and formats do make data management quite difficult for companies. Hence, the need for robust DataOps tools to automate and simplify data life-cycle phases is of utmost importance at this point. Here are, some of the most important DataOps tools that professionals can use in 2022. Census: Census is the…

If you want to invest in a tech stock then DataOps stock can be the best option, take a look here DataOps refers to the data management practices that control the flow of information from source to value, speeding up the process of deriving value from data. DataOps is not just about the tools and processes; it defines a greater cultural shift that breaks down the complexities between the ‘data backend’ and the ‘data frontend’. If practiced, DataOps tries to solve some of the data management challenges to ensure…