Altexsoft

JUNE 6, 2019

Forecasting demand with machine learning in Walmart. Systems that rely on machine learning are capable of analyzing a multitude of data points, finding subtle patterns (indicating changes in customer preferences, behavior, or satisfaction) which can be non-obvious for a human. Source: Lenovo StoryHub.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

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 Weak Development Team 136

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

Cloudera

DECEMBER 10, 2020

These file formats not only help avoid data duplication into proprietary storage formats but also provide highly efficient storage formats. Multiple analytical engines (data warehousing, machine learning, data engineering, and so on) can operate on the same data in these file formats.

Data 98

Data Technical Review Storage Systems Review 98

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. Solution brief. Cloudera and Accenture Alliance.

Data 86

Data Analytics Cloud Technical Review 86

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” New innovations bring new challenges.

Architecture 106

Architecture Innovation Data Open Source 106

Existek

JANUARY 11, 2022

The innovative approaches in delivering software provided the firm basis for the well-known delivery model SaaS. They introduced many innovative solutions to accelerate AI models at the edge. . Over the following years, they offered different products to cover computing, storage, database, security, data flow, migration, etc.

Azure 52

Azure AWS Cloud How To 52

Cloudera

SEPTEMBER 14, 2020

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Fundamental principles to be successful with Cloud data management. Or so they all claim.

Cloud 111

Cloud Data Compliance Analytics 111

Cloudera

DECEMBER 15, 2022

This enables a range of data stewardship and regulatory compliance use cases. Cloudera’s integration of Apache Iceberg in CDP continues to benefit from new enhancements as we join the community in innovating on this modern table format. Read why the future of data lakehouses is open. Enhanced multi-function analytics.

Cloud 83

Cloud Data Analytics Machine Learning 83

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Read why the future of data lakehouses is open.

Data 92

Data Analytics Machine Learning Artificial Inteligence 92

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

DataRobot

MARCH 16, 2023

To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. Agility and enterprise security, compliance, and governance are often at odds. Why are we focusing on this? Because the current ML lifecycle process is broken.

Data 52

Data Machine Learning Artificial Inteligence Agile 52

Cloudera

DECEMBER 21, 2020

Instead, it is a move towards recognizing those companies that are driving innovation and agility by modernizing their data architecture and optimizing their infrastructure to leverage invaluable insights. This year’s winner, the West Midlands Police, stood out with its groundbreaking data strategy that did both of these things.

Data 99

Data Enterprise Technical Review Cloud 99

O'Reilly Media - Ideas

JANUARY 25, 2024

The real innovation in ChatGPT wasn’t the technology itself (though the models behind it represent a significant breakthrough in AI performance); it was packaging the model as a chatbot. PyTorch, the Python library that has come to dominate programming in machine learning and AI, grew 25%. SQL Server also showed a 5.3%

Trends 111

Trends Technical Review Technology Artificial Inteligence 111

TIBCO - Connected Intelligence

DECEMBER 20, 2021

Given the wealth of enhancements and new products TIBCO has announced this year, we want to offer a recap of 2021 innovations to the TIBCO Connected Intelligence platform. The Connect Portfolio’s Multiple Innovations Spark Growth and Industry Recognition from Four Analysts.

Innovation 26

Innovation Analytics Virtualization Cloud 26

Cloudera

AUGUST 24, 2020

Last week we established the requirement of organizations to not only address their technology needs and to assess their data foundation in doing so, but also the importance of up-skilling their workforce. When building your data foundation, how can you prioritize innovation within a hybrid cloud strategy?

Cloud 83

Cloud Data Government Innovation 83

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Inability to handle unstructured data such as audio, video, text documents, and social media posts. Key features of a data lakehouse.

Architecture 52

Architecture Data Storage Machine Learning 52

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 Architecture Software Review 115

O'Reilly Media - Ideas

MARCH 1, 2023

Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence. When you add searches for Go and Golang, the Go language moves from 15th and 16th place up to 5th, just behind machine learning.

Trends 131

Trends Technical Review Technology Software Review 131

Cloudera

JANUARY 11, 2021

And we want to model it quickly with some historic customer usage data…and oh yeah, it should be about 100TB, per day.”. Shadow IT’ projects crop up in LoBs to overcome rigidity that stifles innovation and progress. SDX is also the key to serve multiple workloads on the same data. Cloudera Machine Learning (CML).

Data 64

Data Pharmaceuticals Open Source Machine Learning 64

AWS Machine Learning - AI

JULY 10, 2024

Imagine this—all employees relying on generative artificial intelligence (AI) to get their work done faster, every task becoming less mundane and more innovative, and every application providing a more useful, personal, and engaging experience. Read more about our commitments to responsible AI on the AWS Machine Learning Blog.

Artificial Inteligence 118

Artificial Inteligence AWS Generative AI Knowledge Base 118

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. The lakehouse platform was founded by the creators of Apache Spark , a processing engine for big data workloads.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Hu's Place - HitachiVantara

JANUARY 15, 2019

This new company will unify the operations of these three companies into a single integrated business as Hitachi Vantara to capitalize on Hitachi’s social innovation capability in both operational technologies (OT) and information technologies (IT). A REST API is built directly into our VSP storage controllers.

Systems Review 72

Systems Review Storage System Software Review 72

Cloudera

MARCH 22, 2022

That technical debt includes silo-ed data warehousing appliances, homegrown tools for data processing, or point solutions used for dedicated workloads such as machine learning. data engineering, data warehousing etc.);

Technical Review 84

Technical Review Strategy Data Analytics 84

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