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?

Analytics 203

Analytics Data Analysis Business Analytics 203

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.

Big Data 190

Big Data Analytics Data eLearning 190

Xebia

NOVEMBER 21, 2024

Challenges of growing Imagine the following scenario, you have a dbt project and you are successfully delivering valuable data to your business stakeholders. These contributors can be from your team, a different analytics team, or a different engineering team. To get started, take a look at our GitHub repository today!

Weak Development Team 130

Weak Development Team Testing Analytics Engineering 130

TechCrunch

MARCH 22, 2021

Like similar startups, y42 extends the idea data warehouse, which was traditionally used for analytics, and helps businesses operationalize this data. At the core of the service is a lot of open source and the company, for example, contributes to GitLabs’ Meltano platform for building data pipelines.

Business Intelligence 244

Business Intelligence Software Review B2B Analytics 244

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.

Data 210

Data Machine Learning Artificial Inteligence Analytics 210

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.

Open Source 213

Open Source Data Engineering Strategic Planning Analytics 213

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

DevOps.com

FEBRUARY 2, 2021

The post Varada Open-Sources Its Workload Analyzer to Help Data Teams Optimize Data Lake Queries appeared first on DevOps.com.

Open Source 87

Open Source Data Big Data Data Engineering 87

InfoWorld

MARCH 8, 2024

LinkedIn has decided to open source its data management tool, OpenHouse, which it says can help data engineers and related data infrastructure teams in an enterprise to reduce their product engineering effort and decrease the time required to deploy products or applications.

Open Source 72

Open Source Tools Data Engineering Storage 72

TechCrunch

APRIL 12, 2022

Union.ai , a startup emerging from stealth with a commercial version of the open source AI orchestration platform Flyte, today announced that it raised $10 million in a round contributed by NEA and “select” angel investors. We need to bridge both these worlds in a structured and repeatable way.”

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

TechCrunch

FEBRUARY 2, 2022

RudderStack , a platform that focuses on helping businesses build their customer data platforms to improve their analytics and marketing efforts, today announced that it has raised a $56 million Series B round led by Insight Partners, with previous investors Kleiner Perkins and S28 Capital also participating.

Data 204

Data Machine Learning Artificial Inteligence Architecture 204

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. Netflix is not the only place where data engineers are solving challenging problems with creative solutions.

Data Engineering 82

Data Engineering Engineering Data Generative AI 82

Perficient

FEBRUARY 13, 2025

Breaking down silos has been a drumbeat of data professionals since Hadoop, but this SAP <-> Databricks initiative may help to solve one of the more intractable data engineering problems out there. SAP has a large, critical data footprint in many large enterprises. However, SAP has an opaque data model.

Government 64

Government Open Source Machine Learning Artificial Inteligence 64

TechCrunch

APRIL 13, 2021

Meroxa , a startup that makes it easier for businesses to build the data pipelines to power both their analytics and operational workflows, today announced that it has raised a $15 million Series A funding round led by Drive Capital. million seed round now brings total funding in the company to $19.2 million. .’

Data 248

Data Software Engineering Open Source Engineering 248

CIO

SEPTEMBER 19, 2024

Goldcast, a software developer focused on video marketing, has experimented with a dozen open-source AI models to assist with various tasks, says Lauren Creedon, head of product at the company. The company isn’t building its own discrete AI models but is instead harnessing the power of these open-source AIs.

CTO Coach 207

CTO Coach Artificial Inteligence Fractional CTO Open Source 207

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 72

Data Engineering Engineering Data Software Engineering 72

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 66

Open Source Analytics Software Review Metrics 66

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20

Dzone - DevOps

NOVEMBER 7, 2023

Databricks is a cloud-based platform designed to simplify the process of building data engineering pipelines and developing machine learning models. It offers a collaborative workspace that enables users to work with data effortlessly, process it at scale, and derive insights rapidly using machine learning and advanced analytics.

Data Engineering 80

Data Engineering Engineering Machine Learning Artificial Inteligence 80

CIO

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Not finding what you’re looking for?

Artificial Inteligence 190

Artificial Inteligence Data Machine Learning Azure 190

TechCrunch

JANUARY 10, 2023

The three co-founders originally launched Metaplane as a “customer success” product that analyzed a company’s data to prevent churn. After going through Y Combinator, and with the pandemic hitting, Metaplane pivoted but continued to build data analytics-focused tools. ” Image Credits: Metaplane.

Data 241

Data Software Review Technical Review Systems Review 241

Altexsoft

APRIL 16, 2021

Later, this data can be: modified to maintain the relevance of what was stored, used by business applications to perform its functions, for example check product availability, etc. used for analytical purposes to understand how our business is running. So, we need a solution that’s capable of representing data from multiple dimensions.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

CIO

SEPTEMBER 2, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CTOvision

JUNE 15, 2015

You know Spark, the free and open source complement to Apache Hadoop that gives enterprises better ability to field fast, unified applications that combine multiple workloads, including streaming over all your data. They also launched a plan to train over a million data scientists and data engineers on Spark.

Open Source 117

Open Source Machine Learning Artificial Inteligence Big Data 117

AWS Machine Learning - AI

NOVEMBER 15, 2024

Principal also used the AWS open source repository Lex Web UI to build a frontend chat interface with Principal branding. Additional integrations with services like Amazon Data Firehose , AWS Glue , and Amazon Athena allowed for historical reporting, user activity analytics, and sentiment trends over time through Amazon QuickSight.

Generative AI 111

Generative AI AWS Groups Artificial Inteligence 111

TechCrunch

AUGUST 8, 2022

Systems, an IT consulting firm focused on data analytics. “Over the years, Livneh saw that many organizations were struggling to manage their data integration needs. Equalum manages data pipelines, leveraging open source packages, including Apache Spark and Kafka to stream and batch data processes.

Company 191

Company Data Cloud Google Cloud 191

CIO

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. You can intuitively query the data from the data lake.

Data 210

Data Technical Advisors Technical Review Artificial Inteligence 210

Battery Ventures

OCTOBER 7, 2020

The research pinpointed some of the mega-trends—including cloud computing and the rise of open-source technology—that are upending today’s huge enterprise-IT market as organizations across industries push to digitize their operations by modernizing their technology stacks.

Open Source 144

Open Source Cloud Google Cloud Azure 144

TechCrunch

DECEMBER 1, 2020

That will include more remediation once problems are identified: that is, in addition to identifying issues, engineers will be able to start automatically fixing them, too. . “Users didn’t know how to organize their tools and systems to produce reliable data products.”

Tools 214

Tools Data Weak Development Team Big Data 214

TechCrunch

MAY 10, 2022

Data science teams are stymied by disorganization at their companies, impacting efforts to deploy timely AI and analytics projects. In a recent survey of “data executives” at U.S.-based With Predibase, we’ve seen engineers and analysts build and operationalize models directly.” healthcare company.”

Artificial Inteligence 235

Artificial Inteligence Machine Learning Off-The-Shelf Training 235

O'Reilly Media - Data

JULY 18, 2018

I list a few examples from the media industry, but there are are numerous new startups that collect aerial imagery, weather data, in-game sports data , and logistics data, among other things. If you are an aspiring entrepreneur, note that you can build interesting and highly valued companies by focusing on data.

Machine Learning 191

Machine Learning Artificial Inteligence Data Marketing 191

O'Reilly Media - Ideas

AUGUST 18, 2020

This is an open question, but we’re putting our money on best-of-breed products. We’ll share why in a moment, but first, we want to look at a historical perspective with what happened to data warehouses and data engineering platforms. Lessons Learned from Data Warehouse and Data Engineering Platforms.

Machine Learning 145

Machine Learning Artificial Inteligence Data Data Engineering 145

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

O'Reilly Media - Ideas

JANUARY 8, 2019

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 109

Trends Data Machine Learning Artificial Inteligence 109

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Cloudera

NOVEMBER 19, 2020

Too often, though, legacy systems cannot deliver the needed speed and scalability to make these analytic defenses usable across disparate sources and systems. For many agencies, 80 percent of the work in support of anomaly detection and fraud prevention goes into routine tasks around data management.

Government 119

Government Artificial Inteligence Machine Learning Data 119