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.

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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 255

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 Definitive Guide to Predictive Analytics

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

Data 134

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

Data 107

Defining Data intelligence: Intelligence about Data, Not from Data

IDC

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.

Data 65

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

The Acceleration of Data and Data Storage Trends

DevOps.com

There’s never been a more exciting time for data. Increasing demands for size, speed, performance and reliance have propelled the data market forward at a faster rate than could have ever been anticipated, and new technologies are making some dreams for data a reality.

Schema Evolution Patterns

Speaker: Alex Rasmussen, CEO, Bits on Disk

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

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 207

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

Data 114

Top Companies Hiring Data Scientists

Coding Dojo

If you ever meet a data scientist, odds are you are meeting a very happy person. The post Top Companies Hiring Data Scientists appeared first on Coding Dojo Blog. All Posts artificial intelligence data science program Data Scientist employers hiring tech companiesIn the three top … Read more >>.

40

Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

MONETIZING ANALYTICS FEATURES: Why Data Visualizations. Data Visualizations Have Gone From Rare to Ubiquitous 1 If DataViz Is Old News, What’s the Future of Analytics? Ubiquitous Five years ago, data visualizations were a powerful way to diferentiate a software.

Data Protection Evolution in the Coming Decade – Part 3

Dell EMC

Now let’s discuss what the attributes of future data protection will look like in the coming years. It will operate wherever the workloads and data reside and at the granularity of the new entities that will be used: containers, functions, micro-services, etc.

Data 67

Defining Data intelligence: Intelligence about Data, Not from Data

IDC

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.

Data 52

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 95

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 186

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.

Data Management: Design Principals

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 82

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 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 100

Predictions 2020: Five Real-Time Data Predictions

DevOps.com

According to Gartner, 85% of big data initiatives end in failure. In 2020, organizations are out of budget and operational runway, and need to start executing and getting the big data recipe right. It is not just about big data; it is about using data differently.

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.

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 136

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 147

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 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 108

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?)

Becoming a Data Company: Back to the Future

DevOps.com

The elegance of the end-state of harmonious synergy between software and data belie the complexity and chaos of the transition we find ourselves in the midst of. The post Becoming a Data Company: Back to the Future appeared first on DevOps.com.

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!

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

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

Speaker: Nils Davis, Principal, NPD Associates

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 77

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 165

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

Martin Fowler

Data 255

Rethinking Data Management in a DevOps Environment

DevOps.com

You often hear data is the new oil. Yet, according to a number of DevOps teams, data issues continue to plague their efforts to continuously integrate, test and deploy frequent software releases. More specifically, issues with persistent data (and its […].

Embedded BI and Analytics: Best Practices to Monetize Your Data

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