Can’t-miss sessions for AWS Summit Chicago

Stackery

AWS Glue is a fully managed extract, transform, and load (ETL) service to prepare and load data for analytics. You can use Glue to generate ETL code in Scala or Python to extract data from the source, transform the data to match the target schema, and load it into the target.

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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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 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.

Top 10 industries for monetizing data: Is yours one of them?

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.

Data 276

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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Simplifying Big Data Projects with Data Virtualization

Data Virtualization

According to Gartner, 60% of all the big data projects fail and according to Capgemini 70% of the big data projects are not profitable. There can only be one conclusion, big data projects are hard!

The ethics of data flow

O'Reilly Media - Data

If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows. Data, even “big data,” doesn’t stay in the same place: it wants to move. We give up our data all the time. Data flows can be very complex.

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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.

Data 213

Embedded BI and Analytics: Best Practices to Monetize Your Data

Speaker: Azmat Tanauli, Senior Director of Product Strategy at Birst

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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Data Visualization in R

The Crazy Programmer

There are many libraries in R language that can be used for making graphs and producing statistical data. There are many steps that have to be taken into consideration for doing data analysis through this language. Data Visualization in R.

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Product thinking in a data platform

Martin Fowler

Distribution of the data ownership and data pipeline implementation into the hands of the business domains raise an important concern around accessibility, usability and harmonization of distributed datasets. Zhamak explains that this is where the learning in applying product thinking and ownership of data assets come in handy.

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Redefining Data Protection

Armughan Ahmad - 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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Quantifying a Culture of Innovation

The data imperative

O'Reilly Media - Data

Ben Sharma shares how the best organizations immunize themselves against the plague of static data and rigid process Continue reading The data imperative

Data 151

Are You Ready For Big Data?

The Accidental Successful CIO

CIOs need to understand what they are going to do with big data Image Credit: Merrill College of Journalism Press Releases. The Challenge Is What To Do With The Data. Changes like “big data” often don’t happen all by themselves. The post Are You Ready For Big Data?

Differentiating via data science

O'Reilly Media - Data

Eric Colson explains why companies must now think very differently about the role and placement of data science in organizations. Continue reading Differentiating via data science

Data 176

Why a data scientist is not a data engineer

O'Reilly Media - Ideas

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering !=

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?)

Data engineering: A quick and simple definition

O'Reilly Media - Data

Get a basic overview of data engineering and then go deeper with recommended resources. As the the data space has matured, data engineering has emerged as a separate and related role that works in concert with data scientists.

Data Scientist Spotlight: Sergey Yurgenson

DataRobot

In this Data Scientist Spotlight, you’re going to meet Sergey Yurgenson , the Director of Advanced Data Science Services at DataRobot. Sergey is a Kaggle Grandmaster who was named one of the top ten Kaggle data scientists in 2012. Data Science

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Data architecture vs backend architecture

Erik Bernhardsson

A modern tech stack typically involves at least a frontend and backend but relatively quickly also grows to include a data platform. This typically grows out of the need for ad-hoc analysis and reporting but possibly evolves into a whole oil refinery of cronjobs, dashboards, bulk data copying, and much more. What generally pushes things into the data platform is (generally) that a number of things are. Why bother with a data platform? The data side: the wild west.

Breaking Down Data Silos

Actian

Are your employees hoarding data (and do they even realize it)? Data silos are one of the biggest issues preventing operational processes from achieving peak productivity and business leaders from making informed decisions. What are data silos? Data silo is a term that refers to independent pockets of data within an organization. Data silos and company culture. Breaking down your data silos starts with understanding how they were initially created.

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What Users Want: How and Why to Build Knowledge into Your Product

Speaker: Nils Davis, Principal, NPD Associates

Usage data allows PMs, the product team, and the whole organization to make better decisions. But what if you don't have that data - such as before you have users? Or, what if the right decision seems to fly in the face of the data you have?

The evolution of data science, data engineering, and AI

O'Reilly Media - Data

The O’Reilly Data Show Podcast: A special episode to mark the 100th episode. This episode of the Data Show marks our 100th episode. Continue reading The evolution of data science, data engineering, and AI

Making data science useful

O'Reilly Media - Ideas

Cassie Kozyrkov explains how organizations can extract more value from their data. Continue reading Making data science useful

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How to Talk to Your Clients About Data Breach

Storagecraft

As an IT pro, you know that data breach is a real risk. If your job is to keep them productive and their data safe, you must know how to broach the topic of data breach. Uncategorized data Data Breach data management DR PR response plan security

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Data protection and innovation

O'Reilly Media - Data

Continue reading Data protection and innovation Eva Kaili outlines the fundamentals of GDPR and applications of blockchain.

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?

The Data Landscape is Fragmented, but Your (Logical) Data Warehouse Doesn’t Have to Be

Data Virtualization

The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms: data lakes, IoT architectures, noSQL and graph data stores, SaaS vendors, etc. Ideas big data Data Governance data management systems data swamps data virtualization Denodo Platform Logical Data Warehouse

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Case studies in data ethics

O'Reilly Media - Data

These studies provide a foundation for discussing ethical issues so we can better integrate data ethics in real life. To help us think seriously about data ethics, we need case studies that we can discuss, argue about, and come to terms with as we engage with the real world.

Encrypted data

I'm Programmer

The post Encrypted data appeared first on I'm Programmer. Programming Funny Images Programming Jokes Data Encryption Difference Between Encryption and Decryption Encrypted data encryption and decryption encryption and decryption algorithm

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Progress for big data in Kubernetes

O'Reilly Media - Data

It has become much more feasible to run high-performance data platforms directly inside Kubernetes. The problem is that data lasts a long time and takes a long time to move. The life cycle of data is very different than the life cycle of applications.

Embedded Analytics, Everywhere

Speaker: Dean Yao, Director of Marketing at Jinfonet

Empower users with better data presentation and exploration for deeper insights into their data. What's the next big trend in analytics software and applications? You've probably used it without even knowing: embedded reporting and analytics.