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.

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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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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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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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 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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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.

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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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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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

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The 5 Levels of Analytics Maturity

data or analysis they need, whether it’s a fundamental tool like Excel. Making data analytics work for. For some users, simple data visualizations and dashboards. We don’t have data yet for Level 4, but. expand self-service data discovery to include every user.

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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Types of Queues in Data Structure

The Crazy Programmer

Queue is an important structure for storing and retrieving data and hence is used extensively among all the data structures. Types of Queues in Data Structure. Priority queue makes data retrieval possible only through a pre determined priority number assigned to the data items.

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Data Storage

I'm Programmer

The post Data Storage appeared first on I'm Programmer. Programming Funny Images Programming Jokes data storage SQL Data StorageSQL Humor. 1 of 5. SQL Clause SQL Clause. So true! So true! SQL vs NoSQL Database - Most Popular Databases in the world. link] ? link] ?.

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

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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.

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

Machine learning on encrypted data

O'Reilly Media - Ideas

The O’Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security. In a recent talk , I described the importance of data, various methods for estimating the value of data, and emerging tools for incentivizing data sharing across organizations.

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.

7 data trends on our radar

O'Reilly Media - Ideas

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 101

New Study: 2018 State of Embedded Analytics Report

In a digital era fueled by data and automation, analytics has evolved from an afterthought to a necessity. their data in the digital era. dashboards and data visualizations, and embedding sophisticated features such as predictive analytics. data sources in the application.

Trends in data, machine learning, and AI

O'Reilly Media - Ideas

The O’Reilly Data Show Podcast: Ben Lorica looks ahead at what we can expect in 2019 in the big data landscape. Lorica also showcased some highlights from our upcoming Strata Data and Artificial Intelligence conferences. Continue reading Trends in data, machine learning, and AI

The future of data warehousing

O'Reilly Media - Data

Executives from Cloudera and PNC Bank look at the challenges posed by data-hungry organizations. Continue reading The future of data warehousing

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.

4 Data Security Mistakes Most Businesses Make

The Crazy Programmer

For years, companies all over the world have used customer data to make important decisions about the direction they should take. The main thing you need to be concerned with when collecting and storing data is keeping it out of the hands of cyber-criminals.

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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.

Building tools for enterprise data science

O'Reilly Media - Ideas

The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science. In this episode of the Data Show , I spoke with Vitaly Gordon , VP of data science and engineering at Salesforce. Continue reading Building tools for enterprise data science

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Data collection and data markets in the age of privacy and machine learning

O'Reilly Media - Data

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. Economic value of data.

The Time for Time Series Data

The post The Time for Time Series Data appeared first on DevOps Toolbox AWS database Influxdata InfluxDB time-series dataMore than four years ago, we launched InfluxDB, an open source time series platform.

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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.

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?)

Handling real-time data operations in the enterprise

O'Reilly Media - Data

Getting DataOps right is crucial to your late-stage big data projects. Data science is the sexy thing companies want. The data engineering and operations teams don't get much love. Let's call these operational teams that focus on big data: DataOps teams.

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.

Building a stronger data ecosystem

O'Reilly Media - Data

Ben Lorica looks at the problems we’re facing as we collect and store data, particularly when our machine learning models require huge amounts of labeled data. Continue reading Building a stronger data ecosystem

Test Data? Get Real

The New Stack

These are tales of data-related defects: when software systems break down due to unanticipated, incoming data exercising the software in unexpected ways. In fact, I’m sure most organizations have dealt with a data-related defect fallout in some form or another. Karun Bakshi.

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?

Breaking Down Data Silos in Your Organization

Today’s organizations can finally use advanced technologies to unlock the true value of all of their data. The post Breaking Down Data Silos in Your Organization appeared first on Blogs Enterprise DevOps communication data data silos

In the age of AI, fundamental value resides in data

O'Reilly Media - Ideas

The O’Reilly Data Show Podcast: Haoyuan Li on accelerating analytic workloads, and innovation in data and AI in China. Given the large-scale use in China, I also wanted to get Li’s take on the state of data and AI technologies in Beijing and other parts of China.

It's time to establish big data standards

O'Reilly Media - Data

The deployment of big data tools is being held back by the lack of standards in a number of growth areas. Technologies for streaming, storing, and querying big data have matured to the point where the computer industry can usefully establish standards. Rules for joining streams of data.

Lessons in Google search data

O'Reilly Media - Data

Continue reading Lessons in Google search data Seth Stephens-Davidowitz explains how to use Google searches to uncover behaviors or attitudes that may be hidden from traditional surveys.

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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?