Sat.Aug 17, 2019 - Fri.Aug 23, 2019

Big Data Ingestion: Parameters, Challenges, and Best Practices


Businesses are going through a major change where business operations are becoming predominantly data-intensive. As per studies , more than 2.5 quintillions of bytes of data are being created each day. This pace suggests that 90% of the data in the world is generated over the past two years alone.

How can you Convert a Business Problem into a Data Problem? A Successful Data Science Leader’s Guide

Analytics Vidhya

Overview Effectively translating business requirements to a data-driven solution is key to the success of your data science project Hear from a data science. The post How can you Convert a Business Problem into a Data Problem? A Successful Data Science Leader’s Guide appeared first on Analytics Vidhya. Career Data Science business to data data driven solution data science data science leader data science solution data science thought leader

AI Demystification: On Human-Machine Cooperation


Sci-Fi writers, futurologists and IT researchers and practitioners sometimes conceptualize ‘human-level AI’ as the Holy Grail of AI research. The idea of symbiosis between humans and machines is also settled in mass conscience creating new hopes and new phobias.

Automated Business Analysis Is Spotting Insights Humans Missed


Data overload is a growing problem for enterprise businesses. Analysis teams must often work manually to navigate seas of data and generate the specific insights their colleagues request.It can take multiple analysts weeks to gather, integrate and process the data they need.

Assessing and Fostering a Culture of Innovation

Speaker: Magnus Penker, CEO & Founder, Innovation360 Group

Welcome to an interactive empowering session on how to sharpen your future through innovation management, which can help guide your company’s goals. During this webinar, Magnus Penker, international thought leader and author, will dive into how to assess and foster culture and capabilities for innovation.

Lean Data Governance Strategies


The goal of data governance is to ensure the quality, availability, integrity, security, and usability within an organization. The way that you go about this is up to you.

More Trending

Take Advantage Of The Top 16 Sales Graphs And Charts To Boost Your Business


Billionaire Tilman Fertitta walks into the room. You can’t believe this heavyweight, the CEO and sole owner of multiple restaurant franchises, has given you the time of day. Tilman sits down, settles himself, and glances at the clock.

Sales 200

How to be more effective at execution in a wholesale business


Speed may never be more important to your business than it is today. The right data analytics solution can help your team to react quickly to the needs of your customers and the changes in your industry, products and suppliers that influence your business.

Enterprise Architecture is Dead! Long Live Agile EA!


Republished courtesy of Suren Pillay. Orginally published here: [link]. Join Suren at Future Enterprise Systems Africa 2019, 16-17 October, Focus Rooms Sunninghill, Johannesburg ( ). FESA Insights

NLP Essentials: Removing Stopwords and Performing Text Normalization using NLTK and spaCy in Python

Analytics Vidhya

Overview Learn how to remove stopwords and perform text normalization in Python – an essential Natural Language Processing (NLP) read We will explore the.

Encouraging Innovation in an Established Product Culture

Speaker: Richard Cardran, Chief Creative Officer and VP Strategy, HIA Technologies

Innovation is both a process and an outcome. The best way to begin innovating your products is by innovating your internal process. We'll explore the challenges, solutions, and hands-on techniques for becoming a successful "agent of change" within a well-established product culture. We'll examine the importance of UX and user-centric feature analysis, the adaptation of Agile Methodologies to the creative process, as well as a way to drive successful culture change for setting expectations and winning approvals with cross-functional stakeholders. Innovation and Leadership go hand in hand. Join Richard Cardran, Chief Creative Officer and VP Strategy, HIA Technologies, as we assess some case studies to see how to lead with a clear strategy well-defined tactics, and an unbiased understanding of the fundamental question: "why are you innovating?"

What Does the Marriage of Data Analytics and Robotics Bring?


They say robots are conquering the world, and there is some truth in it. Statista expects the robotics market to grow at an annual rate of around 37.4%. If the trend remains, by 2025 the market size will reach almost 500 billion U.S. dollars.

Integrating your tech: is your stack working together to deliver data results?


In a manufacturing or wholesale business, there is a lot of information to keep track of. As an IT manager, you might find that everyone is looking to you for all the answers too, which can be stressful.

Data: The New Weapon Against our Humanity


What does a new device, downloading of an app, signing up on a platform all have in common……the “accepting” of t’s & c’s.

IT 195

The Most Comprehensive Guide to K-Means Clustering You’ll Ever Need

Analytics Vidhya

Overview K-Means Clustering is a simple yet powerful algorithm in data science There are a plethora of real-world applications of K-Means Clustering (a few. The post The Most Comprehensive Guide to K-Means Clustering You’ll Ever Need appeared first on Analytics Vidhya. Machine Learning Python clustering kmeans kmeans clustering kmeans in python machine learning python unsupervised learning

The Magic of Intent: Start Knowing The Goals of Your Users

Speaker: Terhi Hanninen, Senior Product Manager, Zalando, and Dr. Franziska Roth, Senior User Researcher, Zalando

It's important to know your users - what are their preferences, pain points, ultimate goals? With user research and usage data, you can get a great idea of how your users act. The tricky part is, very few users reliably act the same way every time they use your product. Join Terhi Hanninen, Senior Product Manager, and Dr. Franziska Roth, Senior User Researcher at Zalando, as they explain how they were able to reach a new level of user understanding - by taking their user research and segmenting their users by point-in-time intent. You'll leave with a strategy to change how your product team, and organization at large, understands your users.

Why non Data Scientists can lead Data Science teams


I recently discovered a LinkedIn debate over whether or not non-data scientists could lead data science teams. The debate was polarised between those arguing for technical knowledge & those who focussed on leadership skills.

[eBook] Run your business by your data: Electrical suppliers transform using data analytics


According to IBISWorld the electrical wholesale industry generated $219bn in the last 12 months in the US, UK and Australia and has an expected annual grow rate of two per cent. Those using data analytics are reportedly getting a $9 return for every dollar spent.

Tackling the growing gap between technology and humans (Atlassian)


CCO Melbourne CCO New Zealand CCO Sydney 2019

Top Handy SQL Features for Data Scientists


Whenever we hear "data," the first thing that comes to mind is SQL! SQL comes with easy and quick to learn features to organize and retrieve data, as well as perform actions on it in order to gain useful insights. 2019 Aug Tutorials, Overviews Data Science Data Scientist SQL

IT 114

Embedding Operational Reports: Everything Product Managers Should Know

Speaker: Dean Yao, Sr. Director of Product Marketing, Logi Analytics

Businesses are run with analytics - but companies continue to struggle with interpreting, analyzing, and distributing data. Operational reports help get information to the people who need it most, in formats they understand, and in a timeframe that matters. Join the webinar to learn how embedding operational reports can give your users a precisely formatted, ready-to-analyze view of their operational activities. World-class software teams are embedding operational reports to empower end users with interactive data visualizations, detailed information, and highly precise formats that can be shared via email, PDF, print, or online.

Learning, Innovation and Business Change


Creating new knowledge is an intuitive human endeavour and it brings value and change to individuals, companies and society by shedding light the patterns, practices, inconsistencies and paradoxes in the observed world.

Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens.

The Design Thinking Process: Five Stages to Solving Business Problems


The design thinking process is a method of encouraging and improving creative problem-solving. The design thinking process is by no means new. John Edward Arnold, a professor of mechanical engineering and business administration, was one of the first to discuss the concept in as early as the 1950s.

Detecting stationarity in time series data


Explore how to determine if your time series data is generated by a stationary process and how to handle the necessary assumptions and potential interpretations of your result. 2019 Aug Tutorials, Overviews Time Series


Your 2-Part Metrics Audit for High-Value Products

Speaker: Sam McAfee, Product Development Consultant, Startup Patterns

You know what they say: what's measured improves. As product managers we're in a golden age of being able to get all sorts of metrics and run all sorts of experiments. But what are your measurements and analytics focused on? Are they really truly objective? Do they contribute to the ultimate vision of your product? And is everybody clear on that vision? Join Sam McAfee, Product Development Consultant, as he takes you through a two-part measurement audit. First, you'll learn how to make sure your measurements actually align with your product strategy. And second, you'll learn how to evaluate your culture of using measurements, so future experiments will more consistently provide high-value results.

The Paradoxes in AI


Artificial intelligence is riddled with paradoxes. As if the subject is not ethically and technically complex enough, AI also proves challenging in terms of its many self-contradictions. For a technology ruled by logic, AI presents a series of illogical conflicts.

IT 247

Why Big Data Is Essential To Digital Product Sales

Smart Data Collective

Big data is changing the future of the retail industry. One study found that the value of big data in this sector was worth $3.45 billion in 2018. Big data is especially important in the eCommerce industry, since the market is digital. Smart marketers will look at ways to utilize it.

Sales 99

Introduction to Blockchain for DBAs


Blockchain is a distributed, shared, permissioned ledger for recording transactions with consensus, provenance, immutability, and finality. It is the technology that drives virtual currencies like Bitcoin. But its potential spans many more industries and use cases than just virtual currencies.

An Overview of Python’s Datatable package


Modern machine learning applications need to process a humongous amount of data and generate multiple features. Python’s datatable module was created to address this issue. It is a toolkit for performing big data (up to 100GB) operations on a single-node machine, at the maximum possible speed.

Buyer’s Guide for Embedded Analytics

Selecting the right embedded analytics technology in a crowded market filled with sub-categories can be a daunting task. This eBook discusses the top evaluation criteria buyers of embedded analytics need to consider.

5 Ways How Blockchain will Change the Travel Industry


The myriad of companies that are involved in a single customer’s travel plans is one of the main reasons why many people are excited about how blockchain can transform the travel industry.

Essential Branding Guidelines For Aspiring Data Scientists

Smart Data Collective

Data science is one of the most promising career paths of the 21st-century. Over the past year, job openings for data scientists increased by 56%. People that pursue a career in data science can expect excellent job security and very competitive salaries.

Data Stewardship in the Age of Machine Learning


Suppose you are a data steward, responsible for integrating a collection of data sources, S1, …, Sn. Historically, you would perform the following steps: Have your best programmer define a global schema GS, which the various sources will accommodate.