Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. What is late-arriving data? Let’s dive in!

Data Engineering 105

Data Engineering Engineering Data Systems Review 105

Trigent

JUNE 20, 2022

Businesses worldwide are realizing the importance of the considerable volume of data they possess and the need to extract value from it and incorporate it into enhancing Customer Experience or simplifying operational processes for improved results. This is where data engineering services providers come into play.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

TechCrunch

APRIL 6, 2022

Ascend.io , a company developing data automation products for enterprise customers, has raised $31 million in a Series B round led by Tiger Global with participation from Shasta Ventures and existing investor Accel, it announced today. There’s no denying that the pandemic bolstered the adoption of AI and analytics technologies.

Data 230

Data Technical Cofounder Weak Development Team Data Engineering 230

Netflix Tech

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

Data Engineering 69

Data Engineering Engineering Data Software Engineering 69

Perficient

FEBRUARY 13, 2023

Introduction: We often end up creating a problem while working on data. So, here are few best practices for data engineering using snowflake: 1.Transform Using COPY and SNOWPIPE is the fastest and cheapest way to load data. In fact, this is another example of using the right tools. I’m here.

Data Engineering 69

Data Engineering Engineering Data Storage 69

CIO

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

Artificial Inteligence 289

Artificial Inteligence Strategy Data Machine Learning 289

Xebia

DECEMBER 22, 2023

Therefore, we have selected three different views on JIRA data that have proven their value in different organizations. Please remember, that data, while powerful, is context-dependent and only shows a part of the truth. Example: Showing the statuses, the transitions between them with the average time between them.

Weak Development Team 244

Weak Development Team Data Trends Software Review 244

CIO

JUNE 6, 2023

The shortage of data science skills continues to frustrate organizations in their quest to become more data driven. CIO.com’s 2023 State of the CIO research found that data science/analytics is one of the top three tech-related skills CIOs are trying to hire – and 22% said it’s one of the three most difficult to fill.

Data 130

Data Analytics Government Culture 130

Cloudera

DECEMBER 20, 2022

Efficient use of data will therefore be critical to improving the competitiveness and productivity of assets, both traditional and renewable generation. Data efficiency in renewables. Effective use of data can have a direct impact on the cash flow of wind and solar generation companies in areas such as real-time decision making.

Energy 84

Energy Analytics Data Machine Learning 84

CIO

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. How do they bring all of that data together?

Data 238

Data Architecture Government Strategy 238

CIO

DECEMBER 11, 2023

You have to balance the potential benefits of generative AI with significant, important operational issues, such as ensuring patient data privacy and complying with regulatory requirements. Any and all activities that focus on improving patient data, processes and communications are prime for improvement.

Generative AI 189

Generative AI Artificial Inteligence Healthcare Artificial Intelligence 189

Xebia

MARCH 10, 2021

Many organisations have a new ambition to become a data-driven organisation. In essence, this means the organisation wants to make better business decisions based on insights provided by data [4]. Data itself is not able to advise a business for better decision-making. Data & Analytics as a separate business domain.

DevOps 130

DevOps Data Analytics Policies 130

CIO

FEBRUARY 15, 2024

We took it seriously and said we need to have software, data, and AI capabilities,” says Nilles, who signed on to the CDIO role at the time. “We But to achieve Henkel’s digital vision, Nilles would need to attract data scientists, data engineers, and AI experts to an industry they might not otherwise have their eye on.

Artificial Inteligence 344

Artificial Inteligence B2C Machine Learning Artificial Intelligence 344

TechCrunch

MAY 18, 2022

Heartex, a startup that bills itself as an “open source” platform for data labeling, today announced that it landed $25 million in a Series A funding round led by Redpoint Ventures. We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

TechCrunch

SEPTEMBER 13, 2022

This is especially true for data, a universally necessary input for web3 companies, with crypto data firms like Messari reportedly fundraising amid a down market. Goldsky , a data infrastructure company for crypto startups, has raised $20 million in a seed round led by Felicis and Dragonfly Capital.

Company 185

Company Data Infrastructure Engineering 185

TechCrunch

OCTOBER 7, 2021

Increasingly, conversations about big data, machine learning and artificial intelligence are going hand-in-hand with conversations about privacy and data protection. They could see that the longer-term issue would be a growing need and priority for data privacy. “But now we are running into the bottleneck of the data. .

Artificial Inteligence 246

Artificial Inteligence Technical Review Engineering Data 246

CIO

APRIL 12, 2023

By George Trujillo, Principal Data Strategist, DataStax I recently had a conversation with a senior executive who had just landed at a new organization. He had been trying to gather new data insights but was frustrated at how long it was taking. Real-time AI involves processing data for making decisions within a given time frame.

Artificial Inteligence 356

Artificial Inteligence Artificial Intelligence Machine Learning Agile 356

Altexsoft

FEBRUARY 11, 2023

Data is now one of the most valuable assets for any kind of business. 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 is a data architect?

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JUNE 2, 2021

Data pipelines are in high demand in today’s data-driven organizations. As critical elements in supplying trusted, curated, and usable data for end-to-end analytic and machine learning workflows, the role of data pipelines is becoming indispensable.

Data 93

Data Data Engineering Machine Learning Artificial Inteligence 93

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Data 90

Data Analysis Data Engineering Comparison 90

CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). Cold: On-prem infrastructure As they did in 2022, many IT leaders are reducing investments in data centers and on-prem technologies. “We

Budget 363

Budget Artificial Inteligence Technical Review VR 363

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 R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.

Technical Review 247

Technical Review Analytics Innovation Artificial Intelligence 247

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. Iterations of the lakehouse.

Data 94

Data Analytics Open Source Architecture 94

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

Data 113

Data Architecture Analytics Government 113

Cloudera

MARCH 28, 2023

Today’s healthcare is driven as much by the promise of emerging technologies centered on data processing and advanced analytics as by developing new and specialized drugs. Precision healthcare leverages data and AI-powered advanced analytics to predict and prevent disease and to identify the most effective treatments for each patient.

Healthcare 68

Healthcare Data Machine Learning Artificial Inteligence 68

Cloudera

NOVEMBER 16, 2022

Overall, it struck me that while data science is not new, most firms are still defining the mission of the data office and data officer. It’s clear firms seek to leverage data and embrace its potential insights, but most are forging ahead in largely uncharted territory.

Data 82

Data Insurance Metrics eBook 82

TIBCO - Connected Intelligence

APRIL 15, 2021

Data and analytics investments pay off. According to McKinsey, “High-performing organizations are three times more likely than others to say their data and analytics initiatives have contributed at least 20 percent to EBIT.” Twenty percent of earnings before interest and taxes from data and analytics alone!

Analytics 41

Analytics Development Team Review Technical Review Data 41

CIO

APRIL 3, 2023

Digital solutions and data analytics are changing the world of sports entertainment at a rapid clip. From how players train, to how teams make strategic decisions during games, to how venues operate and fans engage, sports organizations are turning to software engineers and data scientists to help transform the sport experience.

Sport 215

Sport Artificial Inteligence Coaching Games 215

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

Machine Learning 98

Machine Learning Artificial Inteligence Data Data Engineering 98

O'Reilly Media - Data

APRIL 11, 2018

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

Data Engineering 280

Data Engineering Engineering Data Artificial Inteligence 280

O'Reilly Media - Ideas

AUGUST 18, 2020

So you need to redesign your company’s data infrastructure. That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. The Two Cultures of Data Tooling. A little of both?

Machine Learning 144

Machine Learning Artificial Inteligence Data Data Engineering 144

TechCrunch

FEBRUARY 7, 2022

Location data is absolutely critical to such strategies, enabling leading enterprises to not only mitigate challenges, but unlock previously unseen opportunities. Throughout the COVID-19 recovery era, location data is set to be a core ingredient for driving business intelligence and building sustainable consumer loyalty.

Business Intelligence 230

Business Intelligence AWS Sustainability Data Engineering 230

CIO

JULY 18, 2023

The CIO’s biggest hiring challenge is clear: “There is simply not enough talent to go around,” says Scott duFour, global CIO of business payments company Fleetcor, for whom positions in areas such as AI, cloud architecture, and data science remain the toughest to fill. S&P Global, for example, is entering its AI 2.0 The net result?

Technical Advisors 244

Technical Advisors Artificial Inteligence Generative AI How To 244

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Data 110

Data Artificial Inteligence Analytics Machine Learning 110

O'Reilly Media - Data

JULY 18, 2018

While models and algorithms garner most of the media coverage, this is a great time to be thinking about building tools in data. In this post I share slides and notes from a keynote I gave at the Strata Data Conference in London at the end of May. Economic value of data.

Machine Learning 137

Machine Learning Artificial Inteligence Data Marketing 137

O'Reilly Media - Ideas

JANUARY 8, 2019

From infrastructure to tools to training, Ben Lorica looks at what’s ahead for data. Whether you’re a business leader or a practitioner, here are key data trends to watch and explore in the months ahead. Increasing focus on building data culture, organization, and training. Cloud for data infrastructure.

Trends 89

Trends Data Machine Learning Artificial Inteligence 89