TechCrunch

OCTOBER 13, 2022

Data engineers have a big problem. Almost every team in their business needs access to analytics and other information that can be gleaned from their data warehouses, but only a few have technical backgrounds. The New York-based startup announced today that it has raised $7.6

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CIO

MARCH 13, 2025

By early 2024, according to a report from Microsoft , 75% of employees reported using AI at work, with 80% of that population using tools not sanctioned by their employers. People feel overwhelmed; they need solutions fast, and if we dont give them the right tools, theyll find their own.

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CIO

MARCH 13, 2025

Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. And the challenge isnt just about finding people with technical skills, says Bharath Thota, partner at Kearneys Digital & Analytics Practice.

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Apiumhub

DECEMBER 9, 2024

Azure Synapse Analytics is Microsofts end-to-give-up information analytics platform that combines massive statistics and facts warehousing abilities, permitting advanced records processing, visualization, and system mastering. What is Azure Synapse Analytics? Why Integrate Key Vault Secrets with Azure Synapse Analytics?

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CIO

DECEMBER 20, 2024

Provide user interfaces for consuming data. Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Real-time analytics. Choose the right tools and technologies.

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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?

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CIO

DECEMBER 10, 2024

to GPT-o1, the list keeps growing, along with a legion of new tools and platforms used for developing and customizing these models for specific use cases. To integrate AI into enterprise workflows, we must first do the foundation work to get our clients data estate optimized, structured, and migrated to the cloud. From Llama3.1

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CIO

JANUARY 17, 2023

It shows in his reluctance to run his own servers but it’s perhaps most obvious in his attitude to data engineering, where he’s nearing the end of a five-year journey to automate or outsource much of the mundane maintenance work and focus internal resources on data analysis. It’s not a good use of our time either.”

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TechCrunch

MARCH 1, 2023

Too often over the last decade, line of business people have been forgotten when it comes to analytics. Even though these folks are the closest to what’s happening with customers, they tend to get left behind when it comes to tools, which are often geared for data scientists or at least people with a deep understanding of data.

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CIO

NOVEMBER 9, 2022

One potential solution to this challenge is to deploy self-service analytics, a type of business intelligence (BI) that enables business users to perform queries and generate reports on their own with little or no help from IT or data specialists. But there are right and wrong ways to deploy and use self-service analytics.

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CIO

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

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Cloudera

JULY 13, 2021

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . Prerequisites for deploying CDP Data Engineering on Azure can be found here.

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Data Engineering Azure Engineering Enterprise 127

Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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CIO

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

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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. But what about dbt?

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CIO

OCTOBER 18, 2023

Putting data to work to improve health outcomes “Predicting IDH in hemodialysis patients is challenging due to the numerous patient- and treatment-related factors that affect IDH risk,” says Pete Waguespack, director of data and analytics architecture and engineering for Fresenius Medical Care North America.

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CIO

FEBRUARY 19, 2025

The early part of 2024 was disappointing when it comes to ROI, says Traci Gusher, data and analytics leader at EY Americas. This is a use case thats been rolled out widely, he says, though not all tools are available to all employees. With these paid versions, our data remains secure within our own tenant, he says.

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Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. Enterprise Data Engineering From the Ground Up. Figure 1: Key component within CDP Data Engineering.

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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.

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TechCrunch

JUNE 17, 2021

Now, three alums that worked with data in the world of Big Tech have founded a startup that aims to build a “metrics store” so that the rest of the enterprise world — much of which lacks the resources to build tools like this from scratch — can easily use metrics to figure things out like this, too.

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CIO

DECEMBER 4, 2024

And since the latest hot topic is gen AI, employees are told that as long as they don’t use proprietary information or customer code, they should explore new tools to help develop software. These tools help people gain theoretical knowledge,” says Raj Biswas, global VP of industry solutions.

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TechCrunch

DECEMBER 1, 2020

DevOps continues to get a lot of attention as a wave of companies develop more sophisticated tools to help developers manage increasingly complex architectures and workloads. “Users didn’t know how to organize their tools and systems to produce reliable data products.”

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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.

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CIO

MARCH 21, 2022

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals.

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CIO

FEBRUARY 25, 2025

Their success was a proof point for us: If you hire the right people and give them the tools and support they need, they can achieve remarkable things even without years of experience. This experience reinforced our belief that technology is a tool, not a replacement for people.

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Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. Data pipelines are composed of multiple steps with dependencies and triggers. New in 2021.

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TechCrunch

DECEMBER 16, 2020

Hightouch , a SaaS service that helps businesses sync their customer data across sales and marketing tools, is coming out of stealth and announcing a $2.1 At its core, Hightouch, which participated in Y Combinator’s Summer 2019 batch, aims to solve the customer data integration problems that many businesses today face.

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TechCrunch

MARCH 22, 2021

The service, which was founded in 2020, integrates with over 100 data sources , covering all the standard B2B SaaS tools from Airtable to Shopify and Zendesk, as well as database services like Google’s BigQuery. And that in turn led him to also found a second company that focused on B2B data analytics.

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CIO

APRIL 22, 2022

Data science gives the data collected by an organization a purpose. Data science vs. data analytics. While closely related, data analytics is a component of data science, used to understand what an organization’s data looks like. The benefits of data science. Data science jobs.

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The Crazy Programmer

NOVEMBER 6, 2021

A cloud architect has a profound understanding of storage, servers, analytics, and many more. They also use tools like Amazon Web Services and Microsoft Azure. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering. AI or Artificial Intelligence Engineer.

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Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

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TechCrunch

MARCH 23, 2022

At that time, the scrappy data analytics company had scooped up $3.5 million in funding to develop its tool for what happens after you’ve collected a bunch of data, namely assembling and organizing it so the data can be analyzed. to make data analytics more accessible. Image Credits: Astonomer.

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Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

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CIO

SEPTEMBER 29, 2022

Managing all of its facets, of course, requires many different approaches and tools to achieve beneficial outcomes, and Mano Mannoochahr, the companyâ??s s SVP and chief data & analytics officer, has a crowâ??s s unique about the [chief data officer] role is it sits at the cross-section of data, technology, and analytics,â??

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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.

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Data Engineering Engineering Data Generative AI 81

Netflix Tech

JULY 15, 2021

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie 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. Kevin, what drew you to data engineering?

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CIO

OCTOBER 13, 2023

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

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