Dataconomy

JANUARY 13, 2017

One of the coolest things about being a data scientist is being industry-agnostic. You could dive into gigabytes or even petabytes of data from any industry and derive meaningful interpretations that may catch even the industry insiders by surprise. When the global financial crisis hit the American market in 2008, few. The post How to avoid the 7 most common mistakes of Big Data analysis appeared first on Dataconomy.

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Eugene Yan

JANUARY 13, 2017

A web app to find similar products based on image.

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Dataconomy

JANUARY 11, 2017

Cognitive Computing: What’s in a Name? Cognitive computing might be one of the many buzzwords that you today hear and see alongside such terms as Artificial Intelligence, Machine Learning, Deep Learning and Big Data. However, quite opposite to these terms, Cognitive computing, as it seems, does not have a clear. The post Cognitive Computing: How to Transform Digital Systems to The Next Level of Intelligence appeared first on Dataconomy.

Deep Learning 193

Deep Learning Deep Learning Artificial Intelligence Artificial Intelligence 193

Dataconomy

JANUARY 16, 2017

This is Part 2 of Data Strategy series discussing “How To” following Part 1 of Data Strategy that dealt with “5 ‘W’s of Data Strategy” Strategy is about doing the right things and tactics is about doing things right. Data Strategy is about doing the right things to distill Data. The post How to Build a Data Strategy Pt.

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

AI

Dataconomy

JANUARY 9, 2017

I am sure you’ve come across many 2016 statistics on Data and Analytics as I have. I’d like to use couple of statistics from IDG’s Enterprise 2016 Data & Analytics Research to start this article. As per their research, 78% of enterprises agree that data strategy, collection & analysis of big. The post How To Build a Data Strategy Pt. I – Your Ticket to Success appeared first on Dataconomy.

Analytics 181

Analytics Analytics Big Data Big Data 181

Dataconomy

JANUARY 20, 2017

IoT data offers answers to a simple question: “Are things changing or staying the same?” There are new data streams generated each day, that make it possible to quantify the formerly unquantifiable. The Internet of Things (IoT) enables us to measure processes and react more quickly to ever-evolving conditions, not. The post Analytics Strategies for the Internet of Things – Getting the most out of IoT Data appeared first on Dataconomy.

Internet of Things 178

Internet of Things Analytics Analytics Data Science 178

Dataconomy

JANUARY 30, 2017

Journey Science, being derived from connected data from different customer activities, has become pivotal for the telecommunications industry, providing the means to drastically improve the customer experience and retention. It has the ability to link together scattered pieces of data, and enhance a telco business’s objectives. Siloed approaches are becoming.

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Dataconomy

JANUARY 23, 2017

Dataconomy has joined forces with Alexandra Deschamps-Sonsino, one of the world’s leading IoT entrepreneurs and influencers, to run an exclusive, 3-day IoT workshop in Berlin, February 24-26, 2017. Alexandra will host an intensive course where she will provide guidance and share everything she knows about how to build a business that offers. The post Why building an IoT product isn’t like anything else appeared first on Dataconomy.

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Internet of Things Data Science 162

Dataconomy

JANUARY 2, 2017

Financial institutions have become data hoarders Banks, hedge funds, and asset managers have become data hoarders. However, many of these firms find it difficult to make use of all of this data. They need tools that can be used to extract information from various internal unstructured content and to democratise. The post Data Hoarding and Alternative Data In Finance – How to Overcome the Challenges appeared first on Dataconomy.

Data Science 160

Data Science 160

Dataconomy

JANUARY 6, 2017

You may not realize it, but your car probably already has some self-driving technologies—even basic ones. For example, many of the newest cars have lane assist or park assist, which can help you avoid unintended lane violations or better ease into parking spots. But those car assistance technologies depend on. The post Infographic: Car Hacking is Not a Thing of The Future appeared first on Dataconomy.

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Database

Dataconomy

JANUARY 18, 2017

Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become entirely ubiquitous. Within this. The post Data Mining for Predictive Social Network Analysis appeared first on Dataconomy.

Data Mining 150

Data Mining Data Mining Data Mining Predictive Analytics 150

Dataconomy

JANUARY 24, 2017

Let’s face it: Women in tech are few and far between. According to a recent ‘Women in Tech’ report, women held 57% of all professional occupations in 2015, yet they held only 25% of all computing occupations. There are, however, those women in tech “unicorns” that magically appear every so. The post Women in Tech Speak Up at Data Natives Tel Aviv appeared first on Dataconomy.

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Dataconomy

JANUARY 18, 2017

Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become entirely ubiquitous. Within this. The post Data Mining for Predictive Social Network Analysis appeared first on Dataconomy.

Data Mining 128

Data Mining Data Mining Data Mining Predictive Analytics 128

Dataconomy

JANUARY 4, 2017

Using tabs or spaces when writing a new line of code has been one of the fiercest battles ever fought among coders. Because we don’t live in a perfect world where everybody indents and aligns according to the same standards, the debate is ultimately reduced to how source-code is displayed in editing software. The post 400,000 GitHub repositories, 1 billion files, 14 terabytes of code: Tabs or spaces?

Data Analysis 118

Data Analysis Data Analysis Data Science 118

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.