CIO

OCTOBER 20, 2023

It was established in 1978 and certifies your ability to report on compliance procedures, how well you can assess vulnerabilities, and your knowledge of every stage in the auditing process. Microsoft also offers certifications focused on fundamentals, specific job roles, or specialty use cases.

SCRUM 344

SCRUM Azure AWS Agile 344

CIO

AUGUST 7, 2023

While the changes to the tech stack are minimal when simply accessing gen AI services, CIOs will need to be ready to manage substantial adjustments to the tech architecture and to upgrade data architecture. Shapers want to develop proprietary capabilities and have higher security or compliance needs.

Generative AI 246

Generative AI Off-The-Shelf Architecture Infrastructure 246

CIO

JULY 14, 2023

Generative AI models like ChatGPT and GPT4 with a plugin model let you augment the LLM by connecting it to APIs that retrieve real-time information or business data from other systems, add other types of computation, or even take action like open a ticket or make a booking.

Generative AI 246

Generative AI Artificial Inteligence Open Source ChatGPT 246

Agile Engine

DECEMBER 27, 2023

Introduction With the growing availability of cloud and AI, the data collected by organizations is now worth its weight in gold. Large-scale, granular, and actionable data analytics is more accessible than ever, but it still comes with numerous challenges. That’s where data analytics consultancies come into play.

Big Data 52

Big Data Analytics Data Analysis 52

Cloudera

JANUARY 27, 2021

Achieving SOC 2 is one of the first milestones on our aggressive security and compliance roadmap. You can expect to see further compliance achievements, including expanding Cloudera’s ISO27001 certification to include CDP Public Cloud, FedRAMP, and more, over the coming quarters. Why is SOC 2 Important?

Cloud 101

Cloud Disaster Recovery Software Review Technical Review 101

Altexsoft

FEBRUARY 11, 2023

The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

OTS Solutions

MARCH 14, 2019

They have started pilot projects that are associated with machine learning algorithms and their role in improving certain aspects of their business such as customer relationships and cyber security. Are any compliance controls put in place? This investment in AI technology is expected to continue. Practice Participatory Design.

Artificial Inteligence 140

Artificial Inteligence Artificial Intelligence Strategy Technical Review 140

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. Building an AI or machine learning model is not a one-time effort.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

NOVEMBER 1, 2022

But supply chain visibility into the millions (or billions) of parts that comprise the hundreds or thousands of devices and weapons systems that make up our military infrastructure is critical to maintaining battle readiness and regulatory compliance. Natural disasters and severe weather have serious impacts on supply chain continuity.

Cloud 83

Cloud Government Storage Analytics 83

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Deep Learning.

Big Data 85

Big Data Technology Tools Cloud 85

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

O'Reilly Media - Ideas

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

Product Management 136

Product Management Artificial Inteligence Machine Learning Software Review 136

Cloudera

JANUARY 19, 2018

Machine Learning in the Age of Big Data. Sean Anderson provides a tutorial on machine learning. From its origins in the 1950’s to today, the age of big data. Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning.

Artificial Inteligence 45

Artificial Inteligence Machine Learning Big Data IoT 45

Xebia

MARCH 10, 2021

Figure 1 shows the skills of a typical data scientist. However, the ‘Computer Science & IT’ skills are ok for the Machine Learning part, but the Software Development skills of a Data Scientist are focussed on the creation of the advanced analytics model.

DevOps 130

DevOps Data Analytics Policies 130

Mentormate

OCTOBER 31, 2023

The allure of the latest machine-learning techniques is undeniable, but without a well-structured approach, you risk getting lost in the technological maze. Finally, it is critical to understand and plan for compliance with data regulations such as GDPR, especially for global operations.

Artificial Inteligence 98

Artificial Inteligence Healthcare Budget Training 98

O'Reilly Media - Ideas

JANUARY 25, 2024

PyTorch, the Python library that has come to dominate programming in machine learning and AI, grew 25%. We’ve long said that operations is the elephant in the room for machine learning and artificial intelligence. Interest in operations for machine learning (MLOps) grew 14% over the past year.

Trends 115

Trends Technical Review Technology Artificial Inteligence 115

Altexsoft

MARCH 18, 2021

Transformations may include: data sorting and filtering to get rid of irrelevant items, de-duplicating and cleansing, translating and converting, removing or encrypting to protect sensitive information, splitting or joining tables, etc. These are data engineers who are responsible for implementing these processes. Compliance.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

InnovationM

MAY 14, 2023

Tools like Apache Atlas and Collibra provide features to organize, catalog, and document data assets within the data lake. They help establish data lineage, enable data discovery, and enforce compliance with data governance policies.

Data 52

Data Storage Construction Business Intelligence 52

OpenCredo

MARCH 20, 2020

Security, because we work with sensitive data, client information and intellectual property. We cannot afford for this data to make its way into the wrong hands and must comply with compliance mandates. By making data security usable we also expect to make systems easier to manage, operate and understand. Challenges.

Cloud 40

Cloud Data Weak Development Team Compliance 40

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Cloudera

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Enterprise machine learning.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

NOVEMBER 9, 2021

Traditional statistical methods use mainly internal, historical data to predict trends within relatively stable markets. Meanwhile, machine learning (ML) techniques are capable of processing a wide range of both historical and current data from multiple external and internal sources. Compliance evaluation.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces. This April, 47Lining, announced its Amazon Web Services (AWS) Industrial Time Series Data Connector Quick Start.

Cloud 78

Cloud Google Cloud Azure AWS 78

Altexsoft

FEBRUARY 8, 2021

To support the planning process, predictive analytics and machine learning (ML) techniques can be implemented. We have previously described demand forecasting methods and the role of machine learning solutions in a dedicated article. Comparison between traditional and machine learning approaches to demand forecasting.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Erik Bernhardsson

OCTOBER 27, 2015

If you want to understand the business and generate actionable insights, then in my experience you need pretty much no knowledge of statistics and machine learning. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. It’s very different. and much more.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

If you want to understand the business and generate actionable insights, then in my experience you need pretty much no knowledge of statistics and machine learning. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. It’s very different. and much more.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

O'Reilly Media - Data

MARCH 22, 2018

Over the years, machine learning (ML) has come a long way, from its existence as experimental research in a purely academic setting to wide industry adoption as a means for automating solutions to real-world problems. A deep dive into model interpretation as a theoretical concept and a high-level overview of Skater.

Off-The-Shelf 115

Off-The-Shelf Machine Learning Artificial Inteligence Weak Development Team 115

Altexsoft

JANUARY 14, 2021

What specialists and their expertise level are required to handle a data warehouse? However, all of the warehouse products available require some technical expertise to run, including data engineering and, in some cases, DevOps. ELT approach helps with capturing raw data and then finding the best use case for it.

Backup 115

Backup Azure Software Review Systems Review 115

BPM

JANUARY 18, 2019

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. That augmentation must be in a form attractive to humans while enabling security, compliance, authenticity and auditability. Denis Gagne Trisotech [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Cloudera

MAY 22, 2018

This leads to wasted time and effort during research and collaboration or, worse, compliance risk. With Experiments, data scientists can run a batch job that will: create a snapshot of model code, dependencies, and configuration parameters necessary to train the model. The post Now Available: Cloudera Data Science Workbench Release 1.4

Data 41

Data Load Balancer Machine Learning Artificial Inteligence 41

O'Reilly Media - Ideas

JANUARY 25, 2022

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” And a 17% increase in an established topic is very healthy.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

Cloudera

AUGUST 31, 2021

It outperforms other data warehouses on all sizes and types of data, including structured and unstructured, while scaling cost-effectively past petabytes. Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics.

Data 80

Data Analytics Cloud Technical Review 80

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos. Governance.

Data 46

Data Government Big Data Compliance 46

Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems.

Systems Review 72

Systems Review Storage System Software Review 72

Capgemini

MARCH 31, 2024

The AI evolution: Transforming software engineering In the past year, the landscape of tech has seen unprecedented upheaval. Generative AI (GenAI) has catapulted data science, machine learning, and AI into the limelight, sparking conversations and at all levels of business and democratizing access to the power of AI.

Software Engineering 52

Software Engineering Engineering Software Generative AI 52

Altexsoft

SEPTEMBER 9, 2022

Efficient metadata management ensures data integrity , consistency, trustworthiness, and compliance. You can get more information about data labeling in machine learning from another post (it’s one of the main steps of preparing datasets for ML). Risk management and compliance. Data governance.

Tools 59

Tools Technical Review Software Review Systems Review 59