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 246

Software Engineering Data Engineering DevOps AWS 246

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 246

Software Engineering Data Engineering DevOps AWS 246

Cloudera

JUNE 26, 2023

Over time, using the wrong tool for the job can wreak havoc on environmental health. Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. So which open source pipeline tool is better, NiFi or Airflow?

Tools 76

Tools Data Engineering Analytics Testing 76

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

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

TechCrunch

JANUARY 10, 2023

The need for data observability, or the ability to understand, diagnose and orchestrate data health across various IT tools, continues to grow as organizations adopt more apps and services. After going through Y Combinator, and with the pandemic hitting, Metaplane pivoted but continued to build data analytics-focused tools.

Data 241

Data Software Review Technical Review Systems Review 241

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

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 Google Cloud Cloud 191

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. Data lakes and data warehouses unify large volumes and varieties of data into a central location.

Data 92

Data Analytics Open Source Architecture 92

Datavail

JUNE 8, 2023

Data Summit 2023 was filled with thought-provoking sessions and presentations that explored the ever-evolving world of data. From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

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 But Piero Molino, the co-founder of AI development platform Predibase , says that inadequate tooling often exacerbates them.

Artificial Inteligence 235

Artificial Inteligence Machine Learning Off-The-Shelf Training 235

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

O'Reilly Media - Ideas

AUGUST 18, 2020

This article, which examines this shift in more depth, is an opinionated result of countless conversations with data scientists about their needs in modern data science workflows. The Two Cultures of Data Tooling. This is an open question, but we’re putting our money on best-of-breed products.

Machine Learning 144

Machine Learning Artificial Inteligence Data Data Engineering 144

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Temporal data and time-series analytics.

Big Data 87

Big Data Technology Tools Cloud 87

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.”

Data Engineering 309

Data Engineering Engineering Data CTO Coach 309

Cloudera

JANUARY 19, 2022

Gartner® recognized Cloudera in three recent reports – Magic Quadrant for Cloud Database Management Systems (DBMS), Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases and Critical Capabilities for Cloud Database Management Systems for Operational Use Cases. Download the reports to see the detailed scores .

Report 88

Report Technical Advisors Cloud Analytics 88

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.

Trends 89

Trends Data Machine Learning Artificial Inteligence 89

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Adopting AI can help data quality.

Weak Development Team 128

Weak Development Team Data Technical Review Survey 128

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 Big Data Machine Learning Artificial Inteligence 117

Altexsoft

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

Xebia

JANUARY 9, 2024

dbt is a great tool to do your data transformations, and it is widely adopted within modern data stacks all around the world. However, this requires a lot of custom engineering work and is not an easy task. Besides that you need to create a dashboard on top of this artifact data, to get meaningful insights out of it.

Testing 130

Testing Data Open Source Google Cloud 130

Apiumhub

SEPTEMBER 20, 2023

Tech Conferences Compass Tech Summit – October 5-6 Compass Tech Summit is a remarkable 5-in-1 tech conference, encompassing topics such as engineering leadership, AI, product management, UX, and data engineering that will take place on October 5-6 at the Hungarian Railway Museum in Budapest, Hungary.

Conference 97

Conference Artificial Inteligence UI/UX Machine Learning 97

Hu's Place - HitachiVantara

MAY 10, 2019

Rules based systems become unwieldy as more exceptions and changes are added and are overwhelmed by today’s sheer volume and variety of new data sources. However, in the rush to do this, many of these systems have been poorly architected to address the total analytics pipeline. This is colloquially called data wrangling.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

UruIT

APRIL 27, 2020

We also invite you to access our Business Executive’s Guide to Smart Applications, an in-depth e-book which includes important concepts and definitions concerning AI, ML, and recommended systems, as well as business cases and reviews, evaluating various tools so you are informed when selecting the right solution for your business needs.

Artificial Inteligence 78

Artificial Inteligence Machine Learning Azure Software Review 78

Cloudera

JUNE 7, 2022

Also, Cloudera DataFlow is rated highly in the GigaOm Radar for Streaming Data Platforms. Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform.

Data 110

Data Architecture Analytics Government 110

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

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.

Machine Learning 137

Machine Learning Artificial Inteligence Data Marketing 137

UruIT

JULY 23, 2019

This tool allows devs to work on a web environment already set up, so the team can collaboratively share experiments. Its Amazon SageMaker tool is an interesting option for quickly building, training and deploying machine learning models at scale. Pricing: as the AI Hub is in its Beta version, there is currently no cost to use it.

Artificial Inteligence 81

Artificial Inteligence Machine Learning Azure Software Review 81

Apiumhub

APRIL 8, 2021

Ronald van Loon has been recognized among the top 10 global influencers in Big Data, analytics, IoT, BI, and data science. As the director of Advertisement, he works to help data-driven businesses be more successful. With more than 270,000 followers on Twitter, Borne’s influence in data and analytics is widespread.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

Altexsoft

MARCH 18, 2021

It is the process of collecting raw data from disparate sources, transmitting it to a staging database for conversion, and loading prepared data into a unified destination system. The approach is possible thanks to the modern technologies that allow for storing and processing huge volumes of data in any format.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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

TIBCO - Connected Intelligence

FEBRUARY 18, 2020

TIBCO can help empower everyone from data scientists and citizen data scientists to data engineers to business users to developers with flexible and extensible tools. Enable Innovation with Open Source. Perform Analytics in Real Time. Download a complimentary copy of the report here.

Artificial Inteligence 42

Artificial Inteligence Machine Learning Data Sport 42

Kentik

MAY 23, 2017

Given the advanced capabilities provided by cloud and big data technology, there’s no longer any justification for legacy monitoring appliances that summarize away all the details and force operators to swivel between siloed tools. The skills and resources required for open source don’t match core ISP priorities.

Network 40

Network Open Source Big Data Load Balancer 40

KitelyTech

FEBRUARY 3, 2021

Big data also helps to understand customer behavior by collecting information about users and their behaviors, which is important for online business development. Big data visualization tools can be used to explore relationships and patterns in big data. Database Management.

Big Data 52

Big Data Data Development Business Intelligence 52

O'Reilly Media - Ideas

NOVEMBER 13, 2018

Given the growing interest in data privacy among users and regulators, there is a lot of interest in tools that will enable you to build ML models while protecting data privacy. These tools rely on building blocks, and we are beginning to see working systems that combine many of these building blocks.

Machine Learning 92

Machine Learning Artificial Inteligence Software Review Conference 92

Netflix Tech

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. Can we measure the impact of Inclusion and Diversity initiatives?

Infrastructure 73

Infrastructure Scalability Cloud Data 73

Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Scattered across different storages in various formats, data values don’t talk to each other. There are two main approaches to data integration.

Database Administration 64

Database Administration Strategy Data Technical Review 64