CIO

JUNE 28, 2023

“These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As The team leaned on data scientists and bio scientists for expert support. Belcorp operates under a direct sales model in 14 countries.

Technical Review 236

Technical Review Analytics Innovation Artificial Intelligence 236

CIO

JANUARY 6, 2023

While many factors will impact the starting salary for any given role, including competition, location, corporate culture, and budgets, there are certain things you can look for to make sure you land the talent you want. Companies will have to be more competitive than ever to land the right talent in these high-demand areas.

LAN 358

LAN Systems Administration How To WAN 358

CIO

APRIL 3, 2023

The organization now has data engineers, data scientists, and is investing in cutting-edge technologies like quantum computing. “In In a lot of ways, we felt like outsiders within our own organization, but we knew that was going to be the case, that we could usher in this new culture and organization.”

Sport 203

Sport Artificial Inteligence Coaching Games 203

Dataiku

MAY 20, 2020

Collaboration across teams : Data projects are not only about data, but also require strong involvement from business teams to build experience, generate buy-in, and validate relevance. They also require data engineering and other teams to help with the operationalization steps.

Data 105

Data How To Machine Learning Artificial Inteligence 105

Hu's Place - HitachiVantara

APRIL 11, 2019

Few if any data management frameworks are business focused, to not only promote efficient use of data and allocation of resources, but also to curate the data to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need.

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

InfoQ Culture Methods

SEPTEMBER 6, 2019

Is it all about customer-centric business, or is there any data left? Can we integrate data analytics and customer empathy? This article explores how we can move towards a more customer-centric business and what information we require in order to understand the most valuable thing we have: our customer. By Almudena Rodriguez Pardo.

Analytics 66

Analytics Agile Data Big Data 66

Xebia

MARCH 10, 2021

So, this Data Scientist is not capable to fully implement and operate the model he/she developed. We use the definition from the DevOps Agile Skills Association [2]: DevOps is a CULTURAL and OPERATIONAL model that fosters COLLABORATION to ENABLE high-performance IT to ACHIEVE business goals. What is DevOps?

DevOps 130

DevOps Data Analytics Policies 130

RapidValue

JULY 21, 2019

DataOps is a methodology that helps organizations combine access to information for the employees that consume data and those that provide them. To master DataOps, you are required to overcome the organizational and cultural barriers that separate people from data. DataOps is a people and process paradigm.

Business Transformation 65

Business Transformation Enterprise DevOps Analytics 65

Apiumhub

OCTOBER 7, 2021

Many of them are choosing a combination of agile and domain-driven design, where this idea is predominant. Data Engineering: Building your BI infrastructure from scratch by Estefania Rabadan Martinez – Data Engineer Lead at Hotjar.

Software Review 52

Software Review Software Development Technical Review 52

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Xebia

DECEMBER 22, 2023

Many teams are using Atlassian’s JIRA as an issue tracker, which then becomes a valuable source of information for their daily operations. As a team leader utilizing JIRA, you probably have employed JIRA dashboards to monitor the status of work, usually in context of a (release) planning.

Weak Development Team 244

Weak Development Team Data Trends Software Review 244

Altexsoft

APRIL 13, 2023

For example, you’ll deal with real-time data streams if you want to adopt predictive maintenance which requires constant condition monitoring or implement an RTLS system to continuously track your handling equipment and other assets. to develop all the data architecture and analytics solutions. Data siloes.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

O'Reilly Media - Ideas

MARCH 31, 2020

There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.” Particularly at a company that’s new to AI, part of an AI product manager’s job is helping the organization build the culture it needs to succeed with AI.

Product Management 138

Product Management Artificial Inteligence Machine Learning Software Review 138

CIO

OCTOBER 19, 2022

John Hill, CIDO of MSC Industrial Supply, spends less of his time thinking deeply about technology and more about bringing organizational digital agility to MSC. So, at Zebra, we created a hub-and-spoke model, where the hub is data engineering and the spokes are machine learning experts embedded in the business functions.

Leadership 306

Leadership CTO Coach Fractional CTO Culture 306

Coforge

AUGUST 31, 2020

The drastic shift from traditional and orthodox system frameworks and operations can be unarguably attributed to the influx of intelligent technologies such as Artificial Intelligence, Machine Learning, Big Data, Blockchain/DLT led smart contracts, and widespread usage of cloud systems. . Grow — Navigating a Successful Path for Digitization.

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

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

InfoQ Culture Methods

FEBRUARY 24, 2023

In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

Testing 127

Testing Engineering Software Artificial Inteligence 127

InfoQ Culture Methods

FEBRUARY 16, 2023

Have you ever wondered about systems based on machine learning? In those cases, testing takes a backseat. And even if testing is done, it’s done mostly by developers itself. A tester’s role is not clearly portrayed. Testers usually struggle to understand ML-based systems and explore what contributions they can make.

Artificial Inteligence 101

Artificial Inteligence Machine Learning System Testing 101

CIO

APRIL 24, 2023

Fast-forward five years and Merola is now a senior software engineer, writing code, promoting agile practices, and working with business partners to advance The Hartford’s digital agenda. “The The HartCode Academy changed my life and my career path completely,” says Merola. “I

Technical Advisors 278

Technical Advisors Training Recruiting Programming 278

InfoQ Culture Methods

JANUARY 7, 2022

This article presents how to use data science to detect wastes and impediments, and concepts and related information that help teams to figure out the root cause of impediments they struggle to get rid of.

Software Development 111

Software Development Data Software Trends 111

InfoQ Culture Methods

MARCH 19, 2020

The book AI Crash Course by Hadelin de Ponteves contains a toolkit of four different AI models: Thompson Sampling, Q-Learning, Deep Q-Learning and Deep Convolutional Q-learning. It teaches the theory of these AI models and provides coding examples for solving industry cases based on these models. By Ben Linders, Hadelin de Ponteves.

Course 113

Course Software Review Industry Examples 113

Altexsoft

FEBRUARY 10, 2021

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. It covers the entire data analytics lifecycle, from data extraction to visualization and reporting, using Agile practices to speed up business results.

Analytics 75

Analytics DevOps Development Software Review 75

InfoQ Culture Methods

DECEMBER 30, 2019

To be able to improve features in games which are constantly evolving, the challenge will be to scale tests to be on a par with new feature development. Automated tests are vital for King to keep up testing Candy Crush, therefore they are constantly looking for new improved ways to test. By Alexander Andelkovic.

Testing 52

Testing Games Development Case Study 52

Abhishek Tiwari

JULY 20, 2019

When it comes to organising engineering teams, a popular view has been to organise your teams based on either Spotify's agile model (i.e. Both models work on the scale, particularly when the company's core values, priorities, and culture all three are well aligned. product) don't change over a long period.

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61

InfoQ Culture Methods

DECEMBER 6, 2019

As part of the 2019 end-of-year-summary content, this article collects together a list of recommended presentation recordings from the InfoQ editorial team. By Charles Humble, Ben Linders, Arthur Casals, Manuel Pais, Erik Costlow, Shane Hastie, Shaaron A Alvares, Srini Penchikala, Michael Redlich, Steef-Jan Wiggers, Daniel Bryant.

Data Engineering 52

Data Engineering Architecture Programming System 52

Cloudera

APRIL 26, 2023

It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment. The platform offers advanced capabilities for data warehousing (DW), data engineering (DE), and machine learning (ML), with built-in data protection, security, and governance.

Cloud 64

Cloud Data Load Balancer Storage 64

InfoQ Culture Methods

SEPTEMBER 25, 2019

But data doesn’t always engage people; this is where storytelling can help to combine data, insights, and emotion, said Dr. Christine Bailey. She presented techniques to tell compelling stories with data, and showed how that can increase our influence with external and internal stakeholders.

Data 41

Data How To Case Study Data Engineering 41

Altexsoft

JULY 19, 2022

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

OCTOBER 26, 2022

This is how Deloitte defines this role, “The CDO is a catalyst and driver of change, bringing a new culture and mindset, and new ways of working to the enterprise, that would otherwise not have happened or would have happened too slowly.”. Bring culture change. Bring culture change. Data understanding. Project management.

CTO 52

CTO Organization Technical Review Culture 52

Altexsoft

FEBRUARY 8, 2021

Depending on the complexity of your data architecture, consider hiring a business analyst , data engineer , or a team of data scientists to manage your company’s data in a most efficient way. Work on the culture. That, in turn, would drive business agility and accelerate decision-making on all levels.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Cloudera

DECEMBER 18, 2017

“Becoming data-driven is a multi-year journey, not a simple implementation.” Acquiring and using data in a way that simply wasn’t possible up until very recently, requires a huge cultural shift. How do I look across all my silos of data? It’s one of the first things we tell our customers.

Data 40

Data Business Transformation Machine Learning Artificial Inteligence 40

Cloudera

OCTOBER 26, 2023

But unless staff at every level grasp the power of data and have the skills to wield it properly, it becomes a wasted resource. That’s why organizations should focus on creating a culture of data. What can a data-driven culture help organizations accomplish? That’s very important. Here’s how.

Culture 76

Culture Data Company Analytics 76

Altexsoft

MARCH 2, 2023

There’s a centralized structure that provides a framework, which is then used by autonomous departments that own their data and metadata. Benefits include more autonomy, faster issue resolution, and improved agility. Its goal is to define and control all data governance initiatives. sales specialists).

Government 52

Government Tools Data Weak Development Team 52

CIO

JULY 5, 2023

Around the same time of the release, Repsol appointed Juan José Casado Quintero as its new chief digital officer (CDO), another strategic move to digitally transform and accelerate the company’s strategy to become a data-driven company.

Artificial Inteligence 256

Artificial Inteligence Generative AI Energy Strategic Planning 256

Cloudera

MAY 3, 2021

Cloudera sees success in terms of two very simple outputs or results – building enterprise agility and enterprise scalability. Contrast this with the skills honed over decades for gaining access, building data warehouses, performing ETL, creating reports and/or applications using structured query language (SQL). A rare breed.

Scalability 101

Scalability Agile Data Systems Review 101

Altexsoft

DECEMBER 9, 2020

Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

Analytics 102

Analytics Technical Review Technology Applications 102

CIO

AUGUST 3, 2022

Modern delivery is product (rather than project) management , agile development, small cross-functional teams that co-create , and continuous integration and delivery all with a new financial model that funds “value” not “projects.”. Modern delivery. The cloud. The cloud is about more than managing costs.

SDLC 350

SDLC IoT Machine Learning Artificial Inteligence 350