IBM Journey to AI blog

DECEMBER 11, 2023

With a hybrid-cloud architecture, the airlines can deal with fluctuating volumes of data, such as during the busy holiday travel season, which requires scaling up resources and data in real-time to improve workflows and deliver better customer experiences.

DevOps 308

DevOps Automation Generative AI Big Data 308

IBM Journey to AI blog

JULY 24, 2023

This has led to an increase in the importance of IT operations analytics (ITOA), the data-driven process by which organizations collect, store and analyze data produced by their IT services. ITOA turns operational data into real-time insights. Visualization can occur through interactive dashboards or other administration panels.

DevOps 173

DevOps Automation Big Data Data Mining 173

Flipboard

NOVEMBER 22, 2024

The functional architecture with different capabilities is implemented using a number of AWS services, including AWS Organizations , Amazon SageMaker , AWS DevOps services, and a data lake. Solution overview The following diagram illustrates the ML platform reference architecture using various AWS services.

ML 130

ML Data Science Metadata DevOps 130

AI News

JULY 11, 2024

Software development emerges as the most popular area for AI investment (59%), followed by quality assurance (44%) and DevOps and automation (44%). Photo by Nick Fewings ) See also: Microsoft and Apple back away from OpenAI board Want to learn more about AI and big data from industry leaders?

Big Data 152

Big Data Software Development DevOps AI 152

IBM Journey to AI blog

DECEMBER 20, 2023

For instance, a DevOps team can quickly scale or extend an application’s functionality by adding new microservices without having to add a line of code or affecting other aspects of the application. Workloads involving web content, big data analytics and AI are ideal for a hybrid cloud infrastructure.

DevOps 294

DevOps Machine Learning Automation Big Data 294

Pickl AI

APRIL 17, 2023

How can a DevOps team take advantage of Artificial Intelligence (AI)? DevOps is mainly the practice of combining different teams including development and operations teams to make improvements in the software delivery processes. So now, how can a DevOps team take advantage of Artificial Intelligence (AI)?

DevOps 52

DevOps Artificial Intelligence Artificial Intelligence Machine Learning 52

Pickl AI

APRIL 1, 2025

Collaborating with DevOps Teams and Software Developers Cloud Engineers work closely with developers to create, test, and improve applications. Understand DevOps and CI/CD Cloud Engineers often work closely with DevOps teams to ensure smooth deployments. Understanding DevOps concepts will give you an edge in the field.

DevOps 52

DevOps Data Science Automation Big Data 52

IBM Journey to AI blog

SEPTEMBER 5, 2024

Value realization Good data governance aims to maximize the value of data as a strategic asset, enhancing decision-making, big data analytics , machine learning and artificial intelligence projects. DevOps and DataOps are practices that emphasize developing a collaborative culture.

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Metadata Data Quality Auto-classification DevOps 188

IBM Journey to AI blog

AUGUST 6, 2024

Reduced latency: In a serverless environment, code runs closer to the end user, decreasing its latency , which is the amount of time it takes for data to travel from one point to another on a network. Big data analytics Serverless dramatically reduces the cost and complexity of writing and deploying code for big data applications.

DevOps 112

DevOps Big Data Chatbots Artificial Intelligence 112

Flipboard

NOVEMBER 24, 2023

Moreover, the JuMa infrastructure, which is based on AWS serverless and managed services, helps reduce operational overhead for DevOps teams and allows them to focus on enabling use cases and accelerating AI innovation at BMW Group. This results in faster experimentation and shorter idea validation cycles.

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ML DevOps Data Scientist ML Engineer 151

Towards AI

FEBRUARY 10, 2024

Definition of a full-stack data scientist The sibling relationship between data science and software development has led to the borrowing of many concepts from the software development domain into data science practice. Based on these variant role descriptions, we can develop a picture of the full-stack data scientist.

Data Scientist 116

Data Scientist Software Development Data Science Machine Learning 116

Pickl AI

JANUARY 30, 2023

The role of Python is not just limited to Data Science. It’s a universal programming language that finds application in different technologies like AI, ML, Big Data and others. Data Visualization: Use libraries such as Matplotlib, Seaborn, Plotly, etc., to visualize and understand data and model performance.

Python 97

Python DevOps Machine Learning Data Science 97

AWS Machine Learning Blog

MARCH 18, 2025

Eliuth Triana Isaza is a Developer Relations Manager at NVIDIA, empowering Amazons AI MLOps, DevOps, scientists, and AWS technical experts to master the NVIDIA computing stack for accelerating and optimizing generative AI foundation models spanning from data curation, GPU training, model inference, and production deployment on AWS GPU instances.

Generative AI 91

Generative AI DevOps AI Modeling AI 91

AWS Machine Learning Blog

JUNE 25, 2024

She is currently focusing on combining her DevOps and ML background into the domain of MLOps to help customers deliver and manage ML workloads at scale. With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes.

DevOps 117

DevOps Machine Learning LLM Software Engineer 117

IBM Journey to AI blog

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

Computer Vision 247

Computer Vision NLP Robotics Automation 247

IBM Journey to AI blog

JULY 11, 2024

Decision-making AI can help with data-driven decision-making by analyzing large datasets and providing insights that humans might miss. Applied to big data , these advanced analytics can improve strategic planning, risk management and resource allocation.

Artificial Intelligence 122

Artificial Intelligence Artificial Intelligence Automation DevOps 122

AWS Machine Learning Blog

FEBRUARY 1, 2024

She has a diverse background, having worked in many technical disciplines, including software development, agile leadership, and DevOps, and is an advocate for women in tech. He entered the big data space in 2013 and continues to explore that area. He also holds an MBA from Colorado State University.

Generative AI 133

Generative AI Prompt Engineering Prompt Engineer AI 133

Pickl AI

JUNE 29, 2023

It initiates the collection, indexing, and analysis of machine-generated data in real-time. It helps harness the power of big data and turn it into actionable intelligence. Moreover, it allows users to ingest data from different sources. Additionally, Splunk can process and index massive volumes of data.

Big Data 52

Big Data DevOps Data Analysis Machine Learning 52

IBM Journey to AI blog

JULY 11, 2024

Decision-making AI can help with data-driven decision-making by analyzing large datasets and providing insights that humans might miss. Applied to big data , these advanced analytics can improve strategic planning, risk management and resource allocation.

Artificial Intelligence 100

Artificial Intelligence Artificial Intelligence Automation DevOps 100

IBM Journey to AI blog

AUGUST 12, 2024

While microservices offers greater control over the development environment, it also requires a higher level of expertise for developers when it comes to DevOps , the methodology that enables application development. Big data analytics Serverless dramatically reduces the cost and complexity of writing and deploying code for data applications.

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Software Development Artificial Intelligence Artificial Intelligence DevOps 112

AWS Machine Learning Blog

MARCH 5, 2025

He has touched on most aspects of these projects, from infrastructure and DevOps to software development and AI/ML. He collaborates closely with enterprise customers building modern data platforms, generative AI applications, and MLOps. Beyond work, he values quality time with family and embraces opportunities for travel.

Generative AI 76

Generative AI LLM AI AI 76

AWS Machine Learning Blog

FEBRUARY 2, 2024

Abdullahi holds a MSC in Computer Networking from Wichita State University and is a published author that has held roles across various technology domains such as DevOps, infrastructure modernization and AI. In entered the Big Data space in 2013 and continues to explore that area.

ETL 115

ETL DevOps LLM Generative AI 115

ODSC - Open Data Science

OCTOBER 9, 2024

AI for DevOps and CI/CD: Streamlining the Pipeline Continuous Integration and Continuous Delivery (CI/CD) are essential components of modern software development, and AI is now helping to optimize this process. In the world of DevOps, AI can help monitor infrastructure, analyze logs, and detect performance bottlenecks in real-time.

Software Engineer 40

Software Engineer Software Development DevOps Machine Learning 40

AWS Machine Learning Blog

NOVEMBER 14, 2023

In the era of big data and AI, companies are continually seeking ways to use these technologies to gain a competitive edge. At the core of these cutting-edge solutions lies a foundation model (FM), a highly advanced machine learning model that is pre-trained on vast amounts of data.

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ML LLM Natural Language Processing Machine Learning 112

AWS Machine Learning Blog

AUGUST 31, 2023

His core area of focus includes Machine Learning, DevOps, and Containers. He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes. Ram Vittal is a Principal ML Solutions Architect at AWS.

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ML Data Scientist Machine Learning Data Science 115

ODSC - Open Data Science

JULY 24, 2023

This is done using their “3D” approach: DevOps, design, and digital transformation. Lil Projects Lil Projects provides businesses with a set of services aimed at using data science, automation, and AI to empower companies to optimize their campaigns and generate returns.

Data Science 52

Data Science Chatbots Automation Big Data 52

AWS Machine Learning Blog

APRIL 11, 2023

Alberto Menendez is an Associate DevOps Consultant in Professional Services at AWS. Rajesh Ramchander is a Senior Data & ML Engineer in Professional Services at AWS. He helps customers migrate big data and AL/ML workloads to AWS. In her spare time, she enjoys reading and being outdoors.

IDP 85

IDP Explainability Big Data ML 85

Flipboard

MARCH 7, 2023

Each user role such as a data scientist; an ML, MLOps, or DevOps engineer; and an administrator can choose the most suitable approach based on their needs, place in the development cycle, and enterprise guardrails. He develops and codes cloud native solutions with a focus on big data, analytics, and data engineering.

Python 123

Python Data Science Data Scientist ML 123

Marktechpost

JULY 17, 2023

It can also eliminate data silos by providing a single location for structured, semi-structured, and unstructured data. DataRobot All users, including data science and analytics professionals, IT and DevOps teams, executives, and information workers, can collaborate using DataRobot’s AI Cloud Platform.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

The MLOps Blog

JUNE 27, 2023

Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. Delta Lake Delta Lake is an open-source storage layer that provides reliability, ACID transactions, and data versioning for big data processing frameworks such as Apache Spark.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

OCTOBER 20, 2023

The functional architecture with different capabilities is implemented using a number of AWS services, including AWS Organizations , SageMaker, AWS DevOps services, and a data lake. The architecture maps the different capabilities of the ML platform to AWS accounts.

ML 125

ML Data Scientist ML Engineer Data Science 125

ODSC - Open Data Science

JULY 19, 2023

Security: We have included steps and best practices from GitHub’s advanced security scanning and credential scanning (also available in Azure DevOps) that can be incorporated into the workflow. This will help teams maintain the confidentiality of their projects and data.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

AWS Machine Learning Blog

APRIL 21, 2023

She is currently focusing on combining her DevOps and ML background into the domain of MLOps to help customers deliver and manage ML workloads at scale. With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes.

Data Drift 93

Data Drift Metadata Data Quality ML 93

AWS Machine Learning Blog

NOVEMBER 9, 2023

She is passionate about solving customer pain points processing big data and providing long-term scalable solutions. She holds a master’s degree in Data Science from the University of California, Riverside. Saswata Dash is a DevOps Consultant with AWS Professional Services.

Data Drift 120

Data Drift Auto-complete ML Automation 120

AWS Machine Learning Blog

AUGUST 29, 2023

This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account). Refer to Operating model for best practices regarding a multi-account strategy for ML.

Data Scientist 88

Data Scientist Data Quality Python ML 88

AWS Machine Learning Blog

FEBRUARY 21, 2023

She is currently focusing on combining her DevOps and ML background into the domain of MLOps to help customers deliver and manage ML workloads at scale. With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes.

ML 85

ML Software Development Automation Metadata 85

AWS Machine Learning Blog

AUGUST 31, 2023

His core area of focus includes Machine Learning, DevOps, and Containers. He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes. Ram Vittal is a Principal ML Solutions Architect at AWS.

ML 52

ML Data Scientist Machine Learning Data Science 52