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.

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.

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.

Data 247

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

The Science of High-Impact Experimentation

Speaker: Holly Hester-Reilly, Founder and Product Management Coach, H2R Product Science

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.

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

Data 108

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 273

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 208

Announcing Dell EMC Innovations in Data Protection and Data Management

Armughan Ahmad - 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

Data 114

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'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.

Data 206

Data: the New Currency That Accelerates Business

DevOps.com

The amount of data created every day is staggering: 2.5 Cisco Systems estimates that by the end of 2019, IoT will generate more than 500 zettabytes of data per […]. The post Data: the New Currency That Accelerates Business appeared first on DevOps.com.

Data 100

Data Versioning and Pipelines in CD4ML

Martin Fowler

My colleagues continue their article on Continuous Delivery for Machine Learning by looking at the future, considering what further work needs to be done in Data Versioning and Data Pipelines. more…. skip-home-page

Data Management: Design Principals

Armughan Ahmad - Dell EMC

In the recent blog “Redefining Data Protection,” Sharad Rastogi discusses unlocking the value of data capital by evolving data protection to that of a leverageable service to help drive business outcomes. In this context, data protection transitions to data management.

Data 83

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

Speaker: Nils Davis, Principal, NPD Associates

Data Mapping and GDPR: How Are They Related?

DevOps.com

Every business enterprise receives data from an array of diverse data points. The volume of data is growing, and businesses understand the importance of leveraging data and converting them into actionable insights. This is where data mapping takes a precedence.

Data 101

Why Organizations Love Data like Pizza

TIBCO - Connected Intelligence

Organizations Love Data, Too. The same is true with data. For organizations, this is especially so, because data-driven insights are critical to their customer engagement, product innovation, and process optimization success. TIBCO Data Infrastructure that Delivers.

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.

Data 183

5 Steps to Ensuring Validity of Your Business-Critical Data

DevOps.com

Bad data can lead organizations to make mistakes. If your organization isn’t continuously ensuring data is accurate, you can never be sure the business decisions you’re making are smart. So, how do you continuously validate your business data without consuming excessive resources?

Data 89

Embedded BI and Analytics: Best Practices to Monetize Your Data

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

7 Fundamental Steps to Complete a Data Project

Dataiku

It's hard to know where to start once you’ve decided that yes, you want to dive into the fascinating world of data and AI. Data Visualization Data Preparation Data analysis

Data 113

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 135

Cloud Complexities Hinder Effective Enterprise Data Management

DevOps.com

But they’re learning that if APIs are the glue they use to build their systems, data is the fuel that drives these efforts forward. According to data management provider Actian, however, enterprises are experiencing significant challenges when it comes […].

The Value of Visual Data in Decision-Making

DevOps.com

Instinct has ruled business leaders’ mind for a very long time, but as companies expand their business globally, instinct should give way to data as the best measure to remain competitive. We live in a data-driven world.

Data 109

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?

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!

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 145

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

Data 89

Data architecture vs backend architecture

Erik Bernhardsson

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.

Top 7 Free Resources for Data Scientists

Dataiku

Data Scientists are a passionate and curious bunch, who explore the ecosystem to learn new technologies and best practices but you've only got part of the picture if you don't have all the information necessary to understand new industries and technologies.

Data Scientist vs. Data Analyst - What’s the Difference?

Dataiku

Whether you’re a student deciding on a career path, a data analyst looking for a change, or a business owner looking to hire data talent, the question of data scientist vs. data analyst (or business analyst) is a common one. organization data science Data analysis

Data 76

3 Steps to Building Data Science Models

DevOps.com

Have you ever considered supplementing your development skills with some data science? Pick Your Data Game Your first step in learning data science is to find a dataset that fits your […]. The post 3 Steps to Building Data Science Models appeared first on DevOps.com.

Data 114

A Brave New Data-Driven World at Big Data London 2019

TIBCO - Connected Intelligence

“The data universe is expanding. Launch yourself into a brave new data-driven world.” This year’s theme for Big Data LDN (London) challenges organizations to take a data-oriented approach to solve their biggest business challenges. Victory Fueled by Data Keynote.

Iterate Your Way to a Top Analytics Product Experience

Speaker: Richard Cheng, Associate Product Manager, Mark43

Mark43 is on a mission to bring public safety data management into the 21st century. To fix traditionally paper-heavy and error-prone processes, they needed a secure and easy-to-use product experience that simplified and unified crime data collection and management.

How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh

Martin Fowler

Data 246

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.

Data 158

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 to hire a data scientist

Hacker Earth Developers Blog

Data science is one of the most sought after jobs of the 21st century. But how do you hire a data scientist who fits the bill? The key is to have prospective candidates go through the recruiting process quickly, helping close data science positions faster. Data Science.

How To 217

Ask the "Right" Questions: Your Analytics-Guided Product Strategy

Speaker: Yoav Yechiam, Founder and Head Instructor, productMBA