CIO

FEBRUARY 25, 2025

For us, its about driving growth, innovation and engagement through data and technology while keeping our eyes firmly on the business outcomes. What does it mean to be data-forward? Being data-forward is the next level of maturity for a business like ours. Being data-forward isnt just about technology. It wasnt easy.

Data 136

Data Innovation Insurance Culture 136

AWS Machine Learning - AI

NOVEMBER 20, 2024

In today’s data-intensive business landscape, organizations face the challenge of extracting valuable insights from diverse data sources scattered across their infrastructure. The solution combines data from an Amazon Aurora MySQL-Compatible Edition database and data stored in an Amazon Simple Storage Service (Amazon S3) bucket.

Data 111

Data AWS Groups Knowledge Base 111

CIO

MARCH 13, 2025

Thats why we view technology through three interconnected lenses: Protect the house Keep our technology and data secure. For example, when we evaluate third-party vendors, we now ask: Does this vendor comply with AI-related data protections? Are they using our proprietary data to train their AI models?

Company 186

Company Generative AI Insurance Education 186

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. However, they often forget about the fundamental work – data literacy, collection, and infrastructure – that must be done prior to building intelligent data products.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. It’s no longer driven by data volumes, but containerization, separation of storage and compute, and democratization of analytics.

Data Engineering 113

Data Engineering Engineering Data Storage 113

TechCrunch

NOVEMBER 4, 2022

I know this because I used to be a data engineer and built extract-transform-load (ETL) data pipelines for this type of offer optimization. Part of my job involved unpacking encrypted data feeds, removing rows or columns that had missing data, and mapping the fields to our internal data models.

Data 218

Data Storage Analytics Data Engineering 218

Dzone - DevOps

DECEMBER 31, 2024

MLOps, or Machine Learning Operations, is a set of practices that combine machine learning (ML), data engineering, and DevOps to streamline and automate the end-to-end ML model lifecycle. MLOps is an essential aspect of the current data science workflows.

Machine Learning 96

Machine Learning Artificial Inteligence Scalability Data Engineering 96

CIO

OCTOBER 9, 2024

As the technology subsists on data, customer trust and their confidential information are at stake—and enterprises cannot afford to overlook its pitfalls. Yet, it is the quality of the data that will determine how efficient and valuable GenAI initiatives will be for organizations.

Strategy 215

Strategy Data Artificial Inteligence Storage 215

TechCrunch

NOVEMBER 2, 2022

When Berlin-based Y42 launched in 2020 , its focus was mostly on orchestrating data pipelines for business intelligence. “The use case for data has moved beyond ad hoc reporting to become the very lifeblood of a company. .” Image Credits: Y42.

Data 203

Data Business Intelligence Open Source Government 203

TechCrunch

JANUARY 26, 2022

Israeli startup Firebolt has been taking on Google’s BigQuery, Snowflake and others with a cloud data warehouse solution that it claims can run analytics on large datasets cheaper and faster than its competitors. Big data is at the heart of how a lot of applications, and a lot of business overall, works these days.

Analytics 218

Analytics Data Big Data Business Intelligence 218

Cloudera

MAY 3, 2021

Cloudera sees success in terms of two very simple outputs or results – building enterprise agility and enterprise scalability. data is generated – at the Edge. Real-time and time series data is growing 50% faster than static data forms and streaming analytics is projected to grow at a 34% CAGR.

Scalability 103

Scalability Agile Data Systems Review 103

Netflix Tech

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 83

Data Engineering Engineering Data Generative AI 83

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 Data Engineering Sustainability 230

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. CRM platforms). CRM platforms).

Scalability 94

Scalability Data Technical Review Analytics 94

Perficient

APRIL 22, 2025

Data Summit 2025 is just around the corner, and were excited to connect, learn, and share ideas with fellow leaders in the data and AI space. As the pace of innovation accelerates, events like this offer a unique opportunity to engage with peers, discover groundbreaking solutions, and discuss the future of data-driven transformation.

Meeting 52

Meeting Data Serverless Data Engineering 52

CTOvision

MAY 1, 2014

Senior Software Engineer – Big Data. IO is the global leader in software-defined data centers. IO has pioneered the next-generation of data center infrastructure technology and Intelligent Control, which lowers the total cost of data center ownership for enterprises, governments, and service providers.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

TechCrunch

MARCH 7, 2023

With little understanding of the engineering environment, the first logical step should be hiring data scientists to map and plan the challenges that the team may face. However, these data scientists usually have no domain knowledge. The organization may not collect, store or manage the data in a way that is “AI friendly.”

Weak Development Team 246

Weak Development Team Case Study Data Engineering ChatGPT 246

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

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 174

Artificial Inteligence Strategy Data Machine Learning 174

Cloudera

SEPTEMBER 2, 2021

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. At Cloudera, we introduced Cloudera Data Engineering (CDE) as part of our Enterprise Data Cloud product — Cloudera Data Platform (CDP) — to meet these challenges. fixed sized clusters).

Data Engineering 85

Data Engineering Performance Engineering Data 85

Xebia

NOVEMBER 21, 2024

dbt (data build tool) has seen increasing use in recent years as a tool to transform data in data warehouses. Challenges of growing Imagine the following scenario, you have a dbt project and you are successfully delivering valuable data to your business stakeholders.

Weak Development Team 130

Weak Development Team Testing Analytics Engineering 130

TechCrunch

APRIL 26, 2021

Faculty , a VC-backed artificial intelligence startup, has won a tender to work with the NHS to make better predictions about its future requirements for patients, based on data drawn from how it handled the COVID-19 pandemic. We are, I believe, a really effective and scalable AI company, not just for the U.K. and in Europe, Asia.

Artificial Inteligence 231

Artificial Inteligence Machine Learning Artificial Intelligence Scalability 231

CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 195

Analytics Data Engineering Machine Learning Artificial Inteligence 195

CIO

JANUARY 22, 2024

For healthcare organizations, what’s below is data—vast amounts of data that LLMs will have to be trained on. This is where the healthcare industry has a distinct advantage because payers and providers are sitting on an enormous amount of existing data. In fact, the average hospital produces 50 petabytes of data a year.

Generative AI 147

Generative AI Healthcare Fractional CTO Artificial Inteligence 147

Apiumhub

DECEMBER 9, 2024

Azure Key Vault Secrets integration with Azure Synapse Analytics enhances protection by securely storing and dealing with connection strings and credentials, permitting Azure Synapse to enter external data resources without exposing sensitive statistics. Data Lake Storage (Gen2): Select or create a Data Lake Storage Gen2 account.

Azure 91

Azure Analytics Storage Machine Learning 91

Confluent

JUNE 18, 2019

Software projects of all sizes and complexities have a common challenge: building a scalable solution for search. For this reason and others as well, many projects start using their database for everything, and over time they might move to a search engine like Elasticsearch or Solr. You might be wondering, is this a good solution?

Scalability 97

Scalability Architecture Machine Learning Artificial Inteligence 97

Capgemini

NOVEMBER 21, 2024

Snowflake and Capgemini powering data and AI at scale Capgemini October 13, 2020 Organizations slowed by legacy information architectures are modernizing their data and BI estates to achieve significant incremental value with relatively small capital investments. What is data estate modernization?

Data 52

Data Government Innovation Architecture 52

AWS Machine Learning - AI

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. The chatbot improved access to enterprise data and increased productivity across the organization.

Generative AI 113

Generative AI AWS Groups Artificial Inteligence 113

Xebia

JANUARY 30, 2025

Automate Sensitive Data Protection with Metadata-Driven Masking using dbt and Databricks Data Access Management is hard One of the core jobs of a data professional is to handle data responsibly. Consequently, you want to be in control of who can / cannot access your data.

Data 130

Data Groups Data Engineering Systems Review 130

Xebia

JULY 29, 2024

Introduction Data modelers frequently communicate in terms of entities, constraints, and other technical terms. Data modelers need input from the business to understand what data is important and how it should be used. Data modelers need input from the business to understand what data is important and how it should be used.

Technical Review 130

Technical Review Data Systems Review Meeting 130

AWS Machine Learning - AI

MARCH 13, 2025

However, customer interaction data such as call center recordings, chat messages, and emails are highly unstructured and require advanced processing techniques in order to accurately and automatically extract insights. MaestroQA integrated Amazon Bedrock into their existing architecture using Amazon Elastic Container Service (Amazon ECS).

Generative AI 113

Generative AI CTO Coach AWS Artificial Inteligence 113

Cloudera

MARCH 2, 2021

However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data. This data engineering skillset typically consists of Java or Scala programming skills mated with deep DevOps acumen. A rare breed. The difficulty with querying streams.

Data 112

Data Weak Development Team Data Engineering Enterprise 112

Apiumhub

JANUARY 26, 2022

Data engineer roles have gained significant popularity in recent years. Number of studies show that the number of data engineering job listings has increased by 50% over the year. And data science provides us with methods to make use of this data. Who are data engineers?

Data Engineering 52

Data Engineering Engineering Data Machine Learning 52

CIO

APRIL 10, 2024

Inferencing crunches millions or even billions of data points, requiring a lot of computational horsepower. As with many data-hungry workloads, the instinct is to offload LLM applications into a public cloud, whose strengths include speedy time-to-market and scalability. Inferencing and… Sherlock Holmes???

Artificial Inteligence 203

Artificial Inteligence Generative AI Storage Artificial Intelligence 203

TechCrunch

FEBRUARY 23, 2022

Portland, Oregon-based startup thatDot , which focuses on streaming event processing, today announced the launch of Quine , a new MIT-licensed open source project for data engineers that combines event streaming with graph data to create what the company calls a “streaming graph.”

Engineering 190

Engineering Open Source Big Data Fintech 190

CIO

AUGUST 3, 2022

In today’s data economy, in which software and analytics have emerged as the key drivers of business, CEOs must rethink the silos and hierarchies that fueled the businesses of the past. They can no longer have “technology people” who work independently from “data people” who work independently from “sales” people or from “finance.”

Leadership 218

Leadership SDLC IoT Machine Learning 218

Dataiku

JUNE 15, 2022

One key to more efficient, effective AI model and application development is executing workloads on compute platforms that offer high scalability, performance, and concurrency.

Data Engineering 59

Data Engineering Engineering Data Development 59