January, 2020

CCPA 2020: Getting Your Data Landscape Ready


To all BI professionals, CIOs, CDOs, and everyone else relying on data to run a business: Happy New Year! It’s going to be…interesting. From California’s new data privacy law going into full effect to potential new U.S.


The 12 Rules of DataOps to Avert a DataOops

Kirk Borne

Written by Dr. Kirk Borne. One of my first consulting assignments with my current employer began several years ago. I was part of a team advising a large organization in how to design and implement an enterprise analytics solution group for the organization’s full end-to-end business activities.

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Data Science: Breaking Down The Data Silos


In today’s digitized economy, the capability to utilize data represents a real and indispensable competitive advantage. Organizations are using advanced technologies to unbolt the true value of their data.

5 Thoughts on How to Transition into Data Science from Different Backgrounds

Analytics Vidhya

Overview Looking to transition into data science? Here are 5 paths for a non-data science person to land a role in this space The. The post 5 Thoughts on How to Transition into Data Science from Different Backgrounds appeared first on Analytics Vidhya.

Facebook Causes Continue to Show Little Promise as Fundraising Tools

Data & The House of Horrors


I remember getting excited when it came time for the carnival coming to town. There was always a positivity and goodwill in the air as families brought their little ones to try out the various rides and share a meal.

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Top 5 must-have Data Science skills for 2020


The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.

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Best Dashboard Ideas & Design Examples To Boost Your Business Success


The ability to monitor, visualize, and analyze relevant data gives today’s businesses, across a host of sectors, the power to understand their prospects, make informed decisions, increase efficiencies, and work towards a set of rewarding long term goals.

Three ways a data analytics solution helps with ERP migration


There are many benefits for companies in manufacturing, distribution and retail to invest in enterprise resource planning (ERP) technology, including enhanced automation for the ability to deal with a complex data landscape.

Build your first Machine Learning pipeline using scikit-learn!

Analytics Vidhya

Overview Understand the structure of a Machine Learning Pipeline Build an end-to-end ML pipeline on a real-world data Train a Random Forest Regressor for. The post Build your first Machine Learning pipeline using scikit-learn! appeared first on Analytics Vidhya.

A Brief History of Our Future


Paul Morley. Datacon Africa DataCon Africa Insights Data and Analytics

Intelligent Process Automation: Boosting Bots with AI and Machine Learning

Across all sectors, companies are learning that they can transform their businesses by embracing Intelligent Process Automation, or IPA. With the pairing of AI and RPA, IPA adds a new layer of intelligent decision-making processes to automated RPA tasks. By automating repetitive work, and adding the ability to automate intelligent decision making, intelligent automation frees up your most valuable resources – your employees – to spend more time on higher value and more strategic work. But in order to reap the rewards of Intelligent Process Automation, organizations must first educate themselves and prepare for the adoption of IPA. In our ebook, Intelligent Process Automation: Boosting Bots with AI and Machine Learning.

I wanna be a data scientist, but… how?


It’s easy to say "I wanna be a data scientist," but. where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived?

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Understand the fundamentals of Delta Lake Concept


You might be hearing a lot about Delta Lake nowadays. Yes, it is because of it’s introduction of new features which was not there in Apache Spark earlier. Why is Delta Lake?If If you check here, you can understand that Spark writes are not atomic and data consistency is not guaranteed.

How To Extract Maximum Value Of Your Customer Service Data With Professional Customer Service Reports


“There is only one boss. The customer.” – Sam Walton, Walmart’s founder. Customer experience is slowly but surely exceeding both price and product as the world’s most critical brand differentiator, according to numerous articles over the Internet written by industry experts.

How do businesses make decisions with BI?


By utilizing a fact-based, real-time, singular version of the truth, companies are now empowered to achieve and maintain a competitive edge through the use of industry specific business intelligence. Executives have immediate access to crucial information to make fast and educated decisions.

Building Like Amazon

Speaker: Leo Zhadanovsky, Principal Solutions Architect, Amazon Web Services

Amazon's journey to its current modern architecture and processes provides insights for all software development leaders. To get there, Amazon focused on decomposing for agility, making critical cultural and operational changes, and creating tools for software delivery. The result was enabling developers to rapidly release and iterate software while maintaining industry-leading standards on security, reliability, and performance. Whether you're developing for a small startup or a large corporation, learning the tools for CI/CD will make your good DevOps team great. We are excited to be joined by Leo Zhadanovsky, a Principal Solutions Architect at Amazon Web Services.

4 Applications of Regular Expressions that every Data Scientist should know (with Python code)!

Analytics Vidhya

Overview Regular Expressions or Regex is a versatile tool that every Data Scientist should know about Regex can automate various mundane data processing tasks. The post 4 Applications of Regular Expressions that every Data Scientist should know (with Python code)! appeared first on Analytics Vidhya.

Data Quality in Financial Institutions


In the last decade regulatory requirements in financial services increased significantly. Datacon Africa DataCon Africa Insights Data and Analytics

Microsoft Introduces Project Petridish to Find the Best Neural Network for Your Problem


The new algorithm takes a novel approach to neural architecture search. 2020 Jan Tutorials, Overviews Algorithms Microsoft Neural Networks


Establishing More Trust In 2020 With Blockchain


2020 is here. In the last decade, blockchain has garnered the attention of technologists, entrepreneurs and industry stalwarts, leading to experimentation and exploration. Talk about characteristics of blockchain is diminishing and discussion around use cases are soaring.

6 Steps to Improving Your Application’s Analytics Experience

No one designs bad dashboards and reports on purpose. So why do so many applications have terrible analytics experiences? Download this ebook for secrets to creating dashboards and reports your users will love.

Get The Most Out Of Smart Business Intelligence Reporting


Big data plays a crucial role in online data analysis , business information, and intelligent reporting. Companies must adjust to the ambiguity of data, and act accordingly.

Why IT managers recommend business intelligence software


Advancements in technology have changed the role of the IT department from that of a cost center to a strategic asset. Modern IT managers are developing strategies that match a company’s vision and goals.

Build Your First Text Classification model using PyTorch

Analytics Vidhya

Overview Learn how to perform text classification using PyTorch Understand the key points involved while solving text classification Learn to use Pack Padding feature. The post Build Your First Text Classification model using PyTorch appeared first on Analytics Vidhya.

Corinium Meets: Quantum Metric Head of Behavioural Research Marina Shapira


Ahead of her presentation at CDAO UK, we spoke with Quantum Metric’s Marina Shapira about predictive analytics, why companies should embrace a culture of experimentation how and CAOs and CXOs can work together effectively. What is behavioural research?

Rethinking Information Governance In The Age of Unstructured Enterprise Data

Onna is breaking down how the concept of information governance has evolved and ways today’s businesses can develop a holistic framework to keep up with a rapidly accelerating datasphere.

An Introductory Guide to NLP for Data Scientists with 7 Common Techniques


Data Scientists work with tons of data, and many times that data includes natural language text. This guide reviews 7 common techniques with code examples to introduce you the essentials of NLP, so you can begin performing analysis and building models from textual data.

Is AI the game changer of the Aerospace industry?


Artificial Intelligence, Machine Learning, and Big Data are three of the most transforming technologies in the world. All these technologies have the potential to completely revolutionize the way the world functions.

Utilize The Effectiveness Of Professional Executive Dashboards & Reports


Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway. Geoffrey Moore, Author of Crossing the Chasm & Inside the Tornado.

3 ways advanced data analytics can improve customer service


Quality customer service is the gateway to long-term relationships. By using advanced data analytics you can understand your consumer base, deliver on or exceed expectations and proactively identifying opportunities for improvement.

The Best Sales Forecasting Models for Weathering Your Goals

Every sales forecasting model has a different strength and predictability method. It’s recommended to test out which one is best for your team. This way, you’ll be able to further enhance – and optimize – your newly-developed pipeline. Your future sales forecast? Sunny skies (and success) are just ahead!

Pandas Version 1.0 is Out! Top 4 Features Every Data Scientist Should Know

Analytics Vidhya

Overview Singleton scalar for missing values Dedicated datatype for strings Improved output formats and data summaries Introduction There are only a handful of. The post Pandas Version 1.0 is Out! Top 4 Features Every Data Scientist Should Know appeared first on Analytics Vidhya.

Data Literacy: A Huge Opportunity for the Healthcare Industry


It’s easy to get excited about the many ways AI and advanced analytics will shape the future of healthcare. But the industry has a way to go before these technologies begin having a significant impact on the health of ordinary Americans.

The Book to Start You on Machine Learning


This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context. 2020 Jan Tutorials, Overviews Books Machine Learning

I Cannot Teach You Data Science in 10 Days


A Case Study approach towards understanding Entities & Requirements in Data Science Space. Around four and a half years back, I was struggling to understand the whole concept of Data Science. Coming from a non-Statistics background, I was skeptical, worried and more importantly I was obnoxious.

How Banks Are Winning with AI and Automated Machine Learning

Banks have always relied on predictions to make their decisions. Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. But times are changing. Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the white paper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.