O'Reilly Media - Ideas

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

Cloudera

JANUARY 15, 2021

Overview of Cloudera Data Warehouse. Cloudera Data Warehouse is a cloud-native data warehouse based on the Apache Impala and Apache Hive SQL engines, deployed using a containerized architecture based on Kubernetes. CDW is one of several managed services that comprise the broader Cloudera Data Platform (CDP).

Performance 91

Performance Cloud Data Storage 91

Cloudera

MAY 13, 2021

Importing data from one or multiple systems to apply transformations and then export results to another system is becoming increasingly common—which means these kinds of activities must become more automated and easily repetitive. When evaluating a stream processing engine, consider its processing abstraction capabilities.

Engineering 101

Engineering Comparison Open Source Scalability 101

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Cloudera

FEBRUARY 25, 2021

They need strong data exploration and visualization skills, as well as sufficient data engineering chops to fix the gaps they find in their initial study. The project launches an interactive visualization for exploring the quality of representations extracted using multiple model architectures.

Machine Learning 81

Machine Learning Artificial Inteligence Telecommunications Enterprise 81

Apiumhub

NOVEMBER 20, 2023

As the organizers of the Global Software Architecture Summit , we recognized the significance of introducing this subject in the forthcoming edition. With 16 years of professional experience in software engineering, including roles as CTO and CEO, he has become a prominent speaker at Green Software events in Germany.

Fractional CTO 81

Fractional CTO Software CTO Sustainability 81

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

O'Reilly Media - Ideas

MAY 1, 2019

60 Minutes to Better Product Metrics , July 10. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20. Designing Serverless Architecture with AWS Lambda , June 11-12. Software Architecture by Example , June 18.

Course 46

Course Training Artificial Inteligence Machine Learning 46

RapidValue

JULY 21, 2019

From DevOps to DataOps DataOps can be simply stated as “DevOps for data”. It is a set of practices and technologies that integrate the development and operation of data movement architectures into a continuous process. DataOps aids data practitioners to continuously deliver quality data to applications and business processes.

Business Transformation 65

Business Transformation Enterprise DevOps Analytics 65

CIO

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Organization 241

Organization Technical Review Artificial Inteligence Data 241

Mobilunity

DECEMBER 21, 2022

Data scientists specialize in a variety of tasks that can benefit businesses in different ways. Some of the most noteworthy services they offer include: Data Science and Big Data Consulting. Big data engineer experts review existing data architecture, explore data sources, and analyze data lakes.

Data 52

Data How To Machine Learning Artificial Inteligence 52

Altexsoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

O'Reilly Media - Ideas

DECEMBER 6, 2018

These startups are using tools like cryptography, blockchains, and secure communication to build data networks that enable organizations to share data securely. In the case of deep learning, this usually means trying new neural network architectures, refining parameters, or exploring new optimization techniques.

Technology 76

Technology Artificial Inteligence Machine Learning Hardware 76

TIBCO - Connected Intelligence

APRIL 15, 2021

The moment when a customer moves their mouse to the abandon shopping cart icon is the moment when you need to react—not the next day when you get the website metrics report. Compressing your data capture to analyze to get insight to decide to act cycle is key. Data related regulations continue to grow.

Analytics 41

Analytics Development Team Review Technical Review Data 41

Erik Bernhardsson

OCTOBER 27, 2015

So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. How do you respond when you hear the phrase ‘big data’? Seriously, there’s this weird anti-trend of people bashing big data. The other part of “big data” is that it’s at the far right of the hype cycle.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. How do you respond when you hear the phrase ‘big data’? Seriously, there’s this weird anti-trend of people bashing big data. The other part of “big data” is that it’s at the far right of the hype cycle.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Kentik

APRIL 3, 2018

Networking teams no longer need to be limited by unresponsive tools, aggregated stats, and data deadends. The kprobe agent produces flow data enriched with performance metrics and layer 7 details which are stored in the Kentik Data Engine.

Network 40

Network WAN LAN Policies 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

Kentik

DECEMBER 5, 2016

In a recent blog post by Kentik Solutions Engineer Eric Graham we explained how we “dog food” our own NPM solution to troubleshoot network performance issues within our own cloud-based application. Using the performance metrics from nProbe agents running on each host, we were able to identify a particular switch as the root cause.

Network 40

Network Performance Metrics Software Review 40

Kentik

APRIL 11, 2016

Clustered computing for real-time Big Data analytics. The concept of parallel processing based on a “clustered” multi-computer architecture has a long history dating back at least as far as Gene Amdahl’s work at IBM in the 1960s. For more on how we make it work, see Inside the Kentik Data Engine.).

Big Data 40

Big Data Analytics Network Architecture 40

Existek

SEPTEMBER 28, 2023

Therefore, it’s required to obtain good skills in data science. Model selection and design: AI developers choose appropriate machine learning algorithms and neural network architectures based on the problem at hand. Besides, their responsibilities include considering such factors as data type, volume, complexity, etc.

Artificial Inteligence 52

Artificial Inteligence Development How To Artificial Intelligence 52

Altexsoft

SEPTEMBER 9, 2022

Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. Metadata management components.

Tools 59

Tools Technical Review Software Review Systems Review 59

Kentik

NOVEMBER 16, 2015

KDE handles over 10B flow records/day with a microservice architecture that's optimized using metrics. Here at Kentik, our Kentik Detect service is powered by a multi-tenant big data datastore called Kentik Data Engine. And that leads us to metrics. Health checks and series metrics. A local min?

Metrics 40

Metrics Microservices Linux Architecture 40

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Just a few notes on methodology: This report is based on O’Reilly’s internal “Units Viewed” metric. This has been a strange year.

Trends 114

Trends Technical Review Technology Artificial Inteligence 114

Cloudera

MAY 13, 2021

Performance metrics appear in charts and graphs. . We compare the current run of a job to a baseline derived from performance metrics. Fixed Reports / Data Engineering jobs . Fixed Reports / Data Engineering Jobs. Data Engineering jobs only. Data Engineering jobs. Report Format.

Data Engineering 69

Data Engineering Cloud Weak Development Team Resources 69

Apiumhub

APRIL 1, 2021

It will show you how to treat data as a business asset that requires careful investment if you’re to gain real value. Designing data-intensive applications by Martin Kleppmann. This book helps understand the architecture of today’s data systems and how they can be fit into applications that are data-driven and data-intensive.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Comparison between traditional and machine learning approaches to demand forecasting. Establish KPIs.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Implementation options for data pipelines.

Data 76

Data Storage Analytics Data Center 76

ParkMyCloud

JANUARY 17, 2020

Display a basic understanding of core AWS services, uses, and basic AWS architecture best practices. Can deploy and define metrics, monitoring and logging systems on AWS. . Design and maintain network architecture for all AWS services. AWS Certified Big Data – Speciality. Design and maintain Big Data.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Kentik

APRIL 4, 2023

When evaluating solutions, whether to internal problems or those of our customers, I like to keep the core metrics fairly simple: will this reduce costs, increase performance, or improve the network’s reliability? It’s often taken for granted by network specialists that there is a trade-off among these three facets. Resiliency.

Network 104

Network Load Balancer Cloud Backup 104

Altexsoft

NOVEMBER 9, 2021

Procurement metrics and KPIs. We’ll describe the most essential metrics, but the list is nowhere near exhaustive since every company should choose the ones that fit best, depending on the business size and type. Emergency purchase ratio is a reverse metric. Main procurement KPIs. Supplier-related KPIs. Operational KPIs.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

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

CIO

AUGUST 5, 2022

Klipfolio: Klipfolio is designed to enable users to access and combine data from hundreds of services without writing any code. It leverages pre-built, curated instant metrics and a powerful data modeler, making it a good tool for building custom dashboards. Its ease-of-use makes it a good option for non-designers as well.

Data 300

Data Analytics Travel Business Intelligence 300

Abhishek Tiwari

JULY 20, 2019

For instance, if you are fast-growing VC funded e-commerce startup and your number one business priority is multiplying current growth and performing exceptionally well on key financial metrics charted out by your investors. In this model, software architecture and code ownership is a reflection of the organisational model.

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61

O'Reilly Media - Ideas

MARCH 1, 2023

Methodology This report is based on our internal “units viewed” metric, which is a single metric across all the media types included in our platform: ebooks, of course, but also videos and live training courses. We use units viewed because it measures what people actually do on our platform. growth over 2021.

Trends 132

Trends Technical Review Technology Software Review 132

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. What does the high-performance data project have to do with the real Franz Kafka’s heritage? process data in real time and run streaming analytics. Kafka architecture. Kafka cluster architecture.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93