Data engineers vs. data scientists

O'Reilly Media - Data

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. Overly simplistic venn diagram with data scientists and data engineers.

Data Types

The post Data Types appeared first on Blogs ROELBOB Build data types deployment humor parody programming satire

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Relevant Data

The post Relevant Data appeared first on Blogs ROELBOB

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Domain-driven data architecture

Martin Fowler

Zhamak explains the first part of the data mesh concept - using the ideas behind Domain-Driven Design to structure the data platform. more…. skip-home-page

Data Analytics in the Cloud for Developers and Founders

Speaker: Javier Ramírez, Senior AWS Developer Advocate, AWS

You have lots of data, and you are probably thinking of using the cloud to analyze it. But how will you move data into the cloud? In which format? How will you validate and prepare the data? What about streaming data? Can data scientists discover and use the data? Can business people create reports via drag and drop? Can operations monitor what’s going on? Will the data lake scale when you have twice as much data? Is your data secure? In this session, we address common pitfalls of building data lakes and show how AWS can help you manage data and analytics more efficiently.

Self-serve data platform

Martin Fowler

One of the main concerns of distributing the ownership of data to the domains is the duplicated effort and skills required to operate the data pipelines technology stack and infrastructure in each domain.

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Accelerate Cloud Data Integration with Data Virtualization in the Cloud

Data Virtualization

In my last post, I covered some of the latest best practices for enhancing data management capabilities in the cloud. Despite the increasing popularity of cloud services, enterprises continue to struggle with creating and implementing a comprehensive cloud strategy that.


Democratizing data

O'Reilly Media - Data

Tracy Teal explains how to bring people to data and empower them to address their questions. Continue reading Democratizing data

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Data-Driven Design: an introduction


Data has become a crucial quality property of software systems that software vendors have to consider in each development phase. To fill this gap, we introduce data flows in an architectural description language to enable simple definition of confidentiality constraints. .

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Analyzing COVID19 data with Easy Data Transform

Successful Software

I have continued to make lots of improvements to Easy Data Transform, including: gather , spread , summary and substitute transforms. Here is a video of me using Easy Data Transform to analyze the

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Machine Learning for Builders: Tools, Trends, and Truths

Speaker: Rob De Feo, Startup Advocate at Amazon Web Services

Machine learning techniques are being applied to every industry, leveraging an increasing amount of data and ever faster compute. But that doesn’t mean machine learning techniques are a perfect fit for every situation (yet). So how can a startup harness machine learning for its own set of unique problems and solutions, and does it require a warehouse filled with PhDs to pull it off?

Commvault Extends Data Protection Alliance with Microsoft

Commvault and Microsoft are extending their existing relationship to integrate Commvault’s data protection software with Azure Blob Storage. Azure Blob Storage is a service based on object-based storage optimized for unstructured data.

Book Review: Designing Data-Intensive Applications

Henrik Warne

What a great book Designing Data-Intensive Applications is! There are three parts in the book: Foundations of Data Systems (chapters 1 – 4), Distributed Data (chapters 5 – 9), and Derived Data (chapters 10 – 12). Foundations of Data Systems.

Types of Data Structures

The Crazy Programmer

Data structures are a very important programming concept. They provide us with a means to store, organize and retrieve data in an efficient manner. The data structures are used to make working with our data, easier. There are many data structures which help us with this.

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Redefining Data Protection

Dell EMC

In a world where digital transformation determines winners and losers, businesses continue to create increasingly larger volumes of data, and by way of doing so, have evolved to the point where every organization is now a technology company. Data Center Data Protection Opinions Dell EMC

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5 Early Indicators Your Embedded Analytics Will Fail

thrilled to finally visualize their data. They ask to explore data on their own, create and. share analysis, and connect new data sources to the. requests for new and more complex data visualizations, the ability to customize dashboards, and real-time.

An Introduction to Key Data Science Concepts


Here at Dataiku, we frequently stress the importance of collaboration in building a successful data team. In short, successful data science and analytics are just as much about creativity as they are about crunching numbers, and creativity flourishes in a collaborative environment.

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Doing good data science

O'Reilly Media - Data

Data scientists, data engineers, AI and ML developers, and other data professionals need to live ethical values, not just talk about them. The hard thing about being an ethical data scientist isn’t understanding ethics. It’s doing good data science.

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Fast Provisioning of data through Data Virtualization in the Era of ever-increasing Data Fluidity

Data Virtualization

We are in the midst of a significant transformation in each and every sphere of business. We are witnessing an Industrial 4.0 revolution across the industrial sectors. The way products are getting manufactured is being transformed with automation, robotics, and.

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How Veritone Uses AI To Help The Government Extract Value From Data


Artificial Intelligence Artificial Intelligence Companies Big Data and Analytics News AI artificial intelligence Data facial recognition government machine learning ML NLP transcription VeritoneTired of boring presentations and powerpoint slides? So were we!

Why “Build or Buy?” Is the Wrong Question for Analytics

commit to staffing significant resources in development, support, and keeping up with advances in data. Architecting (and Re-Architecting) So Everything Works Together: If the component you choose to bind data doesn’t work. anyone to analyze data, share insights, and make.

How are Big Data and IoT Interrelated?


There has been rapid growth in the Internet of Things (IoT) and big data technologies amongst organizations and individuals. According to Forbes, it’s predicted that the amount of data generated […].

Data's day of reckoning

O'Reilly Media - Data

Our lives are bathed in data: from recommendations about whom to “follow” or “friend” to data-driven autonomous vehicles. Although we’ve benefited from the use of data in countless ways, it has also created a tension between individual privacy, public good, and corporate profits.

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Upcoming Event: Time Series Data Virtual Summit

The Time Series Data Virtual Summit will bring together InfluxData community members for an unique learning experience focused on the impact of time series data. The post Upcoming Event: Time Series Data Virtual Summit appeared first on

Easy Data Transform v1.6.0

Successful Software

I have been working hard on Easy Data Transform. The installer now includes 32 and 64 bit version of Easy Data Transform for Windows and installs the one appropriate to your operating sytem. In practise, this means you may run out of memory if you get much above a million data values.

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How to Package and Price Embedded Analytics

customers absolutely need advanced capabilities like embedded self-service and the means to pull new data sources into the. and the data feeding them—as well as trigger both. rely on—enabling anyone to analyze data when and where. HOW TO PACKAGE & PRICE EMBEDDED ANALYTICS.

Big Data Project Management: Data Must Flow!


I'm currently researching big data project management in order to better understand what makes big data projects different from other tech related projects. Many if not most organizations still have a lot to learn when it comes to making use of emerging big data analysis techniques.

Announcing Dell EMC Innovations in Data Protection and Data Management

Dell EMC

Today I joined Jeff Clarke on stage at Dell Technologies World to announce major innovations in our data protection portfolio. Data Center Data Protection News Dell EMC

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Defining Data intelligence: Intelligence about Data, Not from Data


IDC has been using the phrase “data intelligence software” to describe a category of capabilities that provide intelligence about data, and the term “data intelligence” has caught on in the industry. But not all definitions of data intelligence are equal.

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How to Get Your Digital Data Game on with DataOps

As a new mindset, methodology and practice within data management, DataOps focuses on improving the communication, integration and automation of data flows to simply and successfully help developers, IT and the business create real-time data experiences and reduce the risk of project failure.

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How King Crushes New Product Development using Data-Driven Insights

Speaker: Ian Thompson, Head of Business Intelligence at King, and Zara Wells, Strategic Customer Success Manager at Looker

Product Managers looking to leverage data to make informed product design decisions can learn a lot from renowned gaming company King, maker of Candy Crush and many other games - even if their product has seemingly no overlap with games. Don't miss King’s data expert (dare we say king?)

CodeSOD: The Data Class

The Daily WTF

For example, imagine you’re browsing a PHP codebase and see something like: $fmtedDate = data::now(); You’d instantly know that something was up, just by seeing a class named data. First, clearly, data is a terrible name for a class. But it’s not handling data at all.

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Primer: Demystifying Data Science

The New Stack

Recently he’s been increasingly involved in data science and AI projects. This is the first part of a series by Levon Paradzhanyan that demystifies data science, machine learning, deep learning, and artificial intelligence down while explaining how they all tie into one another.

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New Data Architectures are too Data-Store-Centric

Data Virtualization

Too often the design of new data architectures is based on old principles: they are still very data-store-centric. They consist of many physical data stores in which data is stored repeatedly and redundantly.

3 Ways DevOps Can Increase the Value of Organizational Data

There’s a reason the term “data mining” came into existence. The post 3 Ways DevOps Can Increase the Value of Organizational Data appeared first on Blogs DevOps Practice accelerated analytics business intelligence data security organizational data parallel processing

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Products for Product People: Best Practices in Analytics

Speaker: Andrew Wynn, Senior Product Manager, Looker

As a product manager, you know how helpful custom tailored data solutions can be to doing your job well. But proper data analytics solutions take work to deliver - it's not as simple as just building a dashboard. Who builds products for the product people?

Healthcare’s Big Data Challenge: How a hybrid data platform can help

Cloudera Engineering

Data—and the ability to ingest, synthesize and analyze it, and use it to solve real-world problems and drive organizational value—is at the heart of this turbulence. . Healthcare’s Big Data Challenge. Migrate healthcare data easily between on-premises and the public or private cloud.