What is Big Data Analytics?

Mixpanel on Data

Companies use big data analytics to uncover new and exciting insights in large and varied datasets. It helps them forecast market trends, identify hidden correlations between data flows, and understand their customers’ preferences in fine detail. Big data also moves fast.

Workplace safety and data analytics

3AG Systems

Back to workplace safety One of the challenges associated with tracking safety comes from the interpretation of safety data. We all want to get home safely, right? For some of us, the worst risk we face at the office is a sore neck from bad posture. But for many others, the risk of serious personal injury on the job site is very real.

4 retail trends supported by data analytics

ScienceSoft

Here, we look at some promising initiatives and explain how data analytics can support them To stay competitive, a retailer should monitor market trends.

Consolidation around Cognos 11.1 and other news from IBM Analytics University

David Menninger's Analyst Perspectives

IBM's Analytics University (held in both Miami and Stockholm) brought about some large changes. Big announcements this year included a consolidation of IBM's Watson Analytics into Cognos 11.1, helping provide some clarity to their analytics offerings, along with new visualizations and better data preparation. For the full breakdown of IBM's Analytics University 2018, and my analysis of all the largest announcements, watch my latest hot take.

Business Intelligence and Data Analytics: Making Use of the Alliance

ScienceSoft

We suggest you consider data analytics trends as well. You have a BI solution implemented, but still check recent BI trends? Wisely done! This gives you a great chance to empower your solution

A Comprehensive Guide to Real-Time Big Data Analytics

ScienceSoft

Our big data consultants have come up with an easy guide to real-time big data analytics. We explain the term and describe a typical architecture, as well as share our thoughts about whether real-time analytics can be a competitive advantage

How To Use Data Analytics To Launch A Sustainable Technology Business

Smart Data Collective

You probably wouldn’t think that data analytics would be the core solution. Many people believe that the fields of big data and green business have little overlap. However, big data could actually be a wonderful solution for many sustainability problems.

And the 2018 EMEA Partner Summit Award Winners are…

Cloudera

Representatives from across the Cloudera ecosystem came together to hear from company executives and EMEA leadership as well as interactive sessions on Machine Learning, AI and Data Analytics, Cloud and Platform as well training and certification opportunities. What an evening!

Sensor data analytics in manufacturing: the ‘why’, the ‘when’ and the ‘how’

ScienceSoft

Sensor data analytics has the potential to turn your manufacturing enterprise into a competitive business. To achieve that, first read this article and learn sensor analytics essentials

Divergent and Convergent Phases of Data Analysis

Simply Statistics

There are often discussions within the data science community about which tools are best for doing data science. A Double Diamond for Data Analysis. In this figure I’ve identified four phases of data analysis that alternate between divergent and convergent forms of thinking.

Silver Sponsor ElegantJ BI Demonstrates Smarten Analytic at Gartner Data & Analytics Summit, June 5-6, Mumbai, India

Smarten

ElegantJ BI, an innovative vendor in Business Intelligence, Augmented Analytics and Augmented Data Preparation, is pleased to announce its participation in the Gartner 2018 INDIA Data & Analytics Summit from 5 – 6th June 2018 in Mumbai, India.

Top Data Trends for 2018 – Part 2

Kirk Borne

In the first half of Top Trends in Data for 2018 , Dr. Kirk Borne, Principal Data Scientist and Executive Advisor for Booz Allen Hamilton, outlined five trends in Data Science and AI from 2017 that are carrying over into 2018, including Machine Intelligence, Hyper-personalization, and more. Behavioral Analytics – Modeling our Hierarchy of Needs. Human behavioral science is older than all of our data and analytics capabilities.

Top Data Trends for 2018 – Part 1

Kirk Borne

What data makes possible today is really much more than what data made possible just a few years ago. In this era of digital everything, data now informs and empowers transformative things all around us. In this first post in a series exclusive to Data Makes Possible, Dr. Kirk Borne, Principal Data Scientist and Executive Advisor for Booz Allen Hamilton, outlines the top 10 trends in Data Science and AI from 2017 that are carrying over into the new year of 2018.

The Netflix Data War

Simply Statistics

” by Shalini Ramachandran and Joe Flint details some of the internal debates within Netflix between the Los Angeles-based content team, which is in charge of developing and marketing new content for the streaming service, and the data team. headquarters argued the company shouldn’t ignore the data, according to people familiar with the discussions. My guess in this case, given the above-quoted example, is that the data team is losing some battles.

In 2018, Data Will Put the Human Back into Human Experience – Part 2

Kirk Borne

In this, the second part of the latest in a series exclusive to Data Makes Possible , Dr. Kirk Borne, Principal Data Scientist for Booz Allen Hamilton, adds onto his explanation of the value proposition of improved human experience in the digital enterprise.

Data is the New Frontier for Performance in Formula One

TIBCO

That’s why leading F1 teams have begun to leverage analytics, both on and off the track. If a driver notices an issue with the car during a race, engineers can use the data collected from the car to pinpoint exactly why and where an issue happened. GB of data.

The Role of Theory in Data Analysis

Simply Statistics

In data analysis, we make use of a lot of theory, whether we like to admit it or not. Even if I’m not directly applying a Normal approximation, knowledge of the central limit theorem will often guide my thinking and help me to decide what to do in a given data analytic situation. In his 1962 paper The Future of Data Analysis , Tukey writes that theory should “guide, not command” the practice of data analysis. What Does a Theory of Data Analysis Look Like?

A New Era in Data Warehousing

Cloudera

How do you know when your Data Warehousing solution is working well? True – millions of credit card transactions are processed within minutes for consistency, fraud and compliance, using petabytes of historical transactions as reference data. We call it ‘Modern Data Warehousing’.

What is predictive analytics?

Mixpanel on Data

Companies use predictive analytics to forecast future events based on past data. Predictive analytics involves data mining, statistics, and machine learning. The predictive analytics process. Like all analytical endeavors, prediction begins with planning.

Creating a Holistic View: Data Consolidation and Integration

Perficient Data & Analytics

The consolidation of data and integration of systems is essential to providing a holistic 360-degree view of patients and members. One organization that understands the challenges associated with bringing data together across a large number of hospitals is Mayo Clinic. They also allow you to bring in data from any vendor source, whether it’s claims, revenue, patient-generated, or other EHRs.

Machine Learning Making Big Moves in Marketing

Rocket-Powered Data Science

Behavioral analytics (predictive and prescriptive). Agile analytics (DataOps). Journey Sciences (using graph and linked data modeling). And check out the many excellent resources and consulting services (in Big Data Analytics, Data Science, Machine Learning, and Machine Intelligence) at Booz Allen Hamilton , to help all of your data-driven campaigns make big moves and move forward more effectively.

Big Data And Analytics Has Been Around Forever! Why Is It Still Important?

Timo Elliott

These are some quick answers to some common questions I get about Business Intelligence, Big Data, and Analytics: Big Data. It’s clear that data is one of the most important assets of the future. All of these things require data and analytics. And we can use new technologies like data orchestration to connect and collect data stored in different silos across the organization so that we can recognize previously unseen patterns.

Inside the Mind and Methodology of a Data Scientist

Birst BI

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. Artificial Intelligence is simply an umbrella term for this collection of analytic methods.

New technologies like AI and machine learning are driving the digital transformationMaking AI Real (Part 1)

Jedox

But it is more than just massive computing power, artificial intelligence with sophisticated algorithms, and tons of data that are propelling this megatrend forward. But even so, companies are only starting to scratch the surface of their data’s true potential.

Meet the newest Data Superheros: The Sixth Annual Data Impact Awards Finalists Are…

Cloudera

Drum roll… Starting from well over 100 nominations, we are excited to announce the finalists for this year’s Data Impact Awards ! Two weeks from today we will announce the winners at the Data Impact Awards Celebration on Tuesday, 11th September the week of Strata Data 2018 , New York.

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline?

Sanjeev Mohan

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? I spent the majority of my time helping clients decide which was the right Hadoop platform and which NoSQL / nonrelational data store to pick for specific use cases.

Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Big Data Technologies and Architectures. Modernizing Analytics and Data Warehousing.

Trending Technologies for BI & Financial Planning and AnalysisMaking AI Real (Part 2)

Jedox

Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive. Analytic Evolution in Enterprise Performance Management. Advanced analytics responds to next-generation requirements.

Data Integration: Taming the Beast of Healthcare

Perficient Data & Analytics

To accomplish this, operational data has to be extracted and integrated. Integrating clinical data at this level of detail requires a (wait for it) monstrous effort. To satisfy these complex reporting and analysis requirements requires finding the needed data in many operating systems then merge it all together in a usable way. Lack of expertise in these areas can adversely affect the quality, accuracy and usability of a data warehouse.

Visualization Tools Help Put Data to Work

Perficient Data & Analytics

Army claim that clinical data visualization is a key component in the usage and delivery of EHRs because it: Presents data in a pleasing, easy-to-understand manner. Makes digesting and sharing data faster and simpler. Researchers with the U.S.

How Are You Analyzing and Adjusting to the Mobile Shopper?

Birst BI

Just as Steve Jobs reinvented an entire industry in 2007 when he introduced a mobile gadget called the iPhone, retailers have an opportunity to reinvent themselves by leveraging data generated by the mobile shopper. and external data (weather, traffic, local events, etc.)

Estimating BI and Analytics Tool Migration Efforts

Jen Underwood

As data continues to grow and exceed current BI and analytics system capabilities, more organizations are adopting big data analytics solutions. Big Data & IoT BI & Analytics Data Visualization Migration Sponsoredby Jen Underwood.

Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

Will you please describe your role at Fractal Analytics? Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers? The data will enable companies to provide more personalized services and product choices.

The Value of Data for Philanthropy

Cloudera

In recent years, we have heard a great deal about how new and sophisticated understanding of how to interpret the onslaught of data produced in the modern age could help us turn the corner on major social and environmental problems. Here are a few examples: The volume of data has exploded.

Q&A with Greg Rahn – The changing Data Warehouse market

Cloudera

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. Let’s talk about big data and Apache Impala. Let’s say they’re not working with large-scale data sets.

Modeling as Proof of Concept (POC)

Perficient Data & Analytics

Even though most of the Data scientists will say that they are two different things and used for different purposes; one is a methodology or a step by step approach to deliver the workable model, and the other is to test your idea to make sure your model is possible. The post Modeling as Proof of Concept (POC) appeared first on Data & Analytics. Advanced Analytics AIE Analytics POC CRISP-DM Data Analytics Lifecycle data science Machine Learning MAD Skills Modeling SEMMA

Building an Open Data Processing Pipeline for IoT

Cloudera

A big part of that architecture deals with the flow and management of data, as well as the insights, actions, and decisions that can be created from data to produce better business outcomes. So today, let’s talk DATA! The open data processing pipeline.

IoT 56

The Data Science Iron Triangle – Modern BI and Machine Learning

Cloudera

Most organizations struggle to unlock data science in the enterprise. To that end, Cloudera offers the Data Science Workbench, a collaborative, scalable, and highly extensible platform for data exploration, analysis, modeling, and visualization. The New Iron Triangle.

The Top 10 Most Popular VISION Blogs of 2017

Cloudera

Before we get too far into 2018, let’s take a look at the ten most popular Cloudera VISION blogs from 2017. We (Mike Olson, Amr Awadallah, Christophe Bisciglia, and Jeff Hammerbacher) started Cloudera because we believe that data makes things that are impossible today, possible tomorrow.

Amazon Knows What You Want to Buy BEFORE You Buy It

Perficient Data & Analytics

The recommendation engine is a common Big Data application that can be leveraged for so many industries who are en route their Digital Transformation. These recommendation engines are tipping point between operational and predictive analytics. Big Data Amazon Personalization