AI & Machine Learning News. 23, September 2019

A Whirlwind Tour of Machine Learning Models

A deep dive into the different machine learning models and when you should use them!

In Part I, Choosing a Machine Learning Model, we talked about the part art, part science of picking the perfect machine learning model.

In Part II, we dive deeper into the different machine learning models you can train and when you should use them!

In general tree-based models perform best in Kaggle competitions. The other models make great candidates for ensembling. For computer vision challenges, CNNs outperform everything. For natural language processing, LSTMs or GRUs are your best bet!

With that said, below is a non-exhaustive laundry list of models to try, along with some context for each model.

2019-09-23 03:48:07.595000+00:00 Read the full story…
Weighted Interest Score: 6.0260, Raw Interest Score: 2.2255,
Positive Sentiment: 0.4899, Negative Sentiment 0.1890

CloudQuant Thoughts… A neat article, even the initial image caught my eye. As an aside, I am not impressed with Medium’s charging for blog posts. I do not think it is going to work for them.

The Answer to Forecasting Bitcoin may lie in Artificial Intelligence

As Bitcoin tries to regain some of the lustre it held in late 2017 when it nearly reached US$20,000 in value, investors are still questioning how to predict such a volatile currency.

As a cryptocurrency, there is no physical form that gives Bitcoin value, so it is impossible to perform traditional fundamental analysis of the currency. Consequently, many investors track the so-called technical trading indicators (geometric patterns constructed from historical prices and trading volumes) in order to understand and predict Bitcoin’s future movement.

Some researchers have found success with large complicated models. But these sometimes have hundreds of variables (or predictors) and it is difficult to determine key factors or test the replicability of such approaches. It’s also hard to understand what factors really drive Bitcoin fluctuations on the market.

2019-09-22 00:00:00 Read the full story…
Weighted Interest Score: 5.2632, Raw Interest Score: 2.5894,
Positive Sentiment: 0.2215, Negative Sentiment 0.2385

CloudQuant Thoughts… Create an Artificial Neural Network (ANN) model to learn from a Moving Average Cross? OK, that’s.. interesting. So because it has no underlying physical form you MUST revert to Technical Analysis? What about sentiment data? Surely that is the greatest driver of Bitcoin prices. Also, I have never met a moving average cross model that I have liked. Maybe I am biased and our machine overlords will prove me wrong.

What’s the Difference Between AI, ML, Deep Learning, and Active Learning?

Today, the terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably. While the terms are related, they mean different things. We map out how they all relate to one another, so your team can find the best candidates, best approaches and best frameworks as you embark upon your AI journey.

AI refers to the concept of machines mimicking human cognition. To reference artificial intelligence is to allude to machines performing tasks that only seemed plausible with human thinking and logic. In the real world, one of the most ubiquitous forms of AI might manifest themselves in the form of conversational AI. Conversation AI may include multimodal inputs (e.g. voice, facial recognition) with multimodal outputs (e.g image, synthesized voice). All of these modalities can be considered part of AI, as well as the integration of these modalities.

Machine learning, deep learning, and active learning, on the other hand, are approaches used to implement AI. If AI is when a computer can carry out a set of tasks based on instruction, ML is a machine’s ability to ingest, parse, and learn from that data itself in order to become more accurate or precise about accomplishing that task.


2019-09-17 00:00:00 Read the full story…
Weighted Interest Score: 5.1358, Raw Interest Score: 2.6119,
Positive Sentiment: 0.3657, Negative Sentiment 0.0174

CloudQuant Thoughts… There is definitely a role for the AI/ML adviser, someone who has a strong overview of exactly what AI, ML, Deep Learning, Neural Networks etc can achieve, how they can achieve it and how it can be actioned into a working structure. This is beyond the current knowledge silo of most C-suite executives and there are ample opportunities out there to advise, direct and demonstrate how these new technologies can help any business take things to a new level.

How machine learning is changing identity theft detection

In the wake of several high-profile data breaches, companies, governments, and cybersecurity experts are calling for a more proactive approach to data protection. Using machine learning and artificial intelligence, cybersecurity experts are detecting identity theft faster and more efficiently than ever before.

The Equifax hack in 2017 marked the beginning of a new era in data security. The sheer scope of the breach—with over 147.7 million Americans affected—embedded a sense of defeatism in data security. Many Americans have become apathetic to losing the privacy of their personal information, yet identity theft remains a $1.48 billion problem. But artificial intelligence (AI) is starting to change how we look at identity left.

2019-09-17 13:02:33+00:00 Read the full story…
Weighted Interest Score: 4.7446, Raw Interest Score: 1.5010,
Positive Sentiment: 0.2040, Negative Sentiment 0.5392

CloudQuant Thoughts… This article tends to focus on post hack phase. The fact is, the majority of high publicity hacks have originated from Phishing expeditions, more recently Lateral Phishing expeditions where the email has been very carefully created to attack a specific firm. Companies like Barracuda have been using AI for years to allow them to lock down private networks. If 99.9% of your network activity comes from one location, be that 1) Office A or b) the continental US, everything outside that should be heavily scrutinized. Multiple failed hits from one location should be logged and analyzed. This is prime real estate for AI. The problem here is not that AI is just catching up, it has been in this space for longer any other space. The problem is humans doing stupid stuff!

HPE’s Armstrong-Barnes: Fraud detection and prevention becoming “significantly more problematic”

Banks and financial institutions are having to cope with increasingly more onerous fraud threats, according to Hewlett Packard Enterprise’s chief technologist for artificial intelligence (AI), Matt Armstrong-Barnes.

Speaking at Sibos in central London, Armstrong-Barnes said more financial firms were being forced to turn to AI to attempt to stem the rising threats.

“We’re seeing a huge drive in back office automation,” he said. “Fraud detection and prevention is becoming significantly more problematic and AI is one of the only ways we can deal with the tsunami of data that’s hit…
2019-09-23 00:00:00 Read the full story…
Weighted Interest Score: 4.6875, Raw Interest Score: 1.6775,
Positive Sentiment: 0.0381, Negative Sentiment 0.3431

UK fintech sector faces talent shortfall

A Census of UK fintech firms by EY and Innovate Finance has found that the sector has continued to attract rising levels of investment despite global economic uncertainty, although major challenges lie ahead in talent recruitment and gender diversity.

Based on a study of over 224 fintech companies, the Census reveals that the average total investment raised by firms grew from £15m in 2017 to more than £20m in 2019 – an increase of a third (33%),…
2019-09-23 10:53:00 Read the full story…
Weighted Interest Score: 4.4426, Raw Interest Score: 1.6454,
Positive Sentiment: 0.2879, Negative Sentiment 0.4525

More Cash for DataRobot Along with ML Ops Tool

High-flying enterprise AI specialist DataRobot announced another huge funding round along with a machine learning platform for managing predictive models that combines internally developed monitoring framework with so-called ML Ops tools acquired earlier this year.

Boston-based DataRobot said Tuesday (Sept. 17) it has added another $206 million to its venture capital war chest, bringing its investment total through seven funding rounds to $431 million. It announced a $100 million Series D funding round last…
2019-09-17 00:00:00 Read the full story…
Weighted Interest Score: 4.3618, Raw Interest Score: 2.5484,
Positive Sentiment: 0.1290, Negative Sentiment 0.0645

Forget “Set and Forget”, instead Cultivate fit-for-purpose AI: Mastercard APAC CTO

Artificial Intelligence (AI) is not new. These days, it would be difficult to find a business that isn’t at least attempting to use AI. However, too often the development of AI is described in a similar way to traditional coding: “compiled,” “built,” and “run”. This implies that AI is built once and then adjusted occasionally as needed.

AI is, however, incredibly dynamic, and requires more than a “set and forget” appro…
2019-09-19 07:16:40+10:00 Read the full story…
Weighted Interest Score: 4.1363, Raw Interest Score: 1.4999,
Positive Sentiment: 0.4144, Negative Sentiment 0.4934

Are We Headed for a 2020 Recession? 2 Ways to Still Find Great Stocks

Jacob: S and P 500 is up 20% year to date with a whole lot of risk out there. What stocks should you be buying now. You’re going to want to hear what are two experts recommend? TheStreet’s Action Alerts PLUS’s portfolio analysts Zev Fima is on tech trends to potential recession, but Hilary Kramer, founder of Kramer Capital Research likes a bunch of value stocks in disguise. Zev, we’ll start with you. How can investors find growth if we get a rece…
2019-09-20 13:39:12-04:00 Read the full story…
Weighted Interest Score: 3.9201, Raw Interest Score: 1.5902,
Positive Sentiment: 0.2959, Negative Sentiment 0.3698

Review of The RegTech Book article, ‘RegTech and the Science of Regulation’

The REGTECH Book: The Financial Technology Handbook for Investors, Entrepreneurs and Visionaries in Regulation, Wiley August 2019. Authors: Janos Barberis, Douglas W. Arner, Ross P. Buckley. Amazon link

My print copy of the long awaited RegTech book ships from Amazon next week and promises to be a comprehensive resource, crowdsourced from more than sixty leading compliance practitioners, banking regulators, and technology entrepreneurs.

What is…
2019-09-20 18:37:37 Read the full story…
Weighted Interest Score: 3.6763, Raw Interest Score: 1.7002,
Positive Sentiment: 0.3142, Negative Sentiment 0.3881

The World’s Premier Analytics and AI Conference for Government Happens in Washington September 25

Date: September 25th, 2019

Location: Washington DC

Website: https://bit.ly/2GNTYPl

Data Driven Government is the world’s premier conference focused on supporting the President’s agenda to use data as a strategic asset. Motivated to help leaders increase efficiency, share and discuss emerging trends, improve evidence-based policy making and more, this conference is practically-focused and vendor-neutral.

This event is meant to bring leaders to…
2019-09-19 13:43:35-05:00 Read the full story…
Weighted Interest Score: 3.5814, Raw Interest Score: 1.8467,
Positive Sentiment: 0.5036, Negative Sentiment 0.1119

Vishal Sikka Raises $50 Million For His AI Startup Vianai From Undisclosed Investors

Former Infosys chief Vishal Sikka’s startup Vianai has reportedly raised $50 million as seed funding from undisclosed investors. Sikka demonstrated a new AI platform vision last week during his keynote address at Oracle Open World. Vianai’s vision is to enable every company, in every industry, to utilize the explorable and explainable AI techniques.

“Companies today have been formed and reshaped by the systems of yesterday,” said Sikka. “In the …
2019-09-23 06:46:34+00:00 Read the full story…
Weighted Interest Score: 3.4349, Raw Interest Score: 1.5012,
Positive Sentiment: 0.2906, Negative Sentiment 0.0484

Choosing a Machine Learning Model

The part art, part science of picking the perfect machine learning model.

The number of shiny models out there can be overwhelming, which means a lot of times people fall back on a few they trust the most and use them on all new problems. This can lead to sub-optimal results.

Today we’re going to learn how to quickly and efficiently narrow down the space of available models to find those that are most likely to perform best on your problem type…
2019-09-23 03:39:50.387000+00:00 Read the full story…
Weighted Interest Score: 3.3428, Raw Interest Score: 1.6090,
Positive Sentiment: 0.3706, Negative Sentiment 0.2145

FinextraTV reveals 3-part Sibos 2019 Highlight Series

rconnected World’. In a 3-part series, we look at the power of AI, the value of Levering Data and the challenges and opportunities around regulation in Financial services. We set out to capture where Artificial Intelligence is impacting most, the concerns it raises and how the industry can use AI to maximum effect in the future. We ask participants about the importance of developing a data strategy, the problems leveraging data overcomes and the new & improved services it leads to. The final part to our series will look at Regulation and how the banks are adapting to today’s regulatory demands, we question who will …
2019-09-22 22:28:00 Read the full story…
Weighted Interest Score: 3.3372, Raw Interest Score: 1.7281,
Positive Sentiment: 0.5760, Negative Sentiment 0.6912

Label and One-Hot-Encoding — Feature Preprocessing for Categorical Features

A dataset may contain both numerical and categorical features. Categorical features need to be transformed into numerical features before they can be used to train a machine learning model as machine learning models are mathematical models and only accept numerical data.

In this post, I will be discussing encoding techniques: label encoding and one-hot-encoding, which are the most commonly used feature preprocessing techniques for transforming categorical features into numerical features, along with example codes. By the end of the post, you will be able to encode categorica…
2019-09-23 04:05:09.447000+00:00 Read the full story…
Weighted Interest Score: 3.3361, Raw Interest Score: 1.9868,
Positive Sentiment: 0.0828, Negative Sentiment 0.0414

Data Governance and Data Discovery: Enabling Data Regulation Implementation

Businesses are continuously striving to leverage data-driven insights or competitive intelligence, the concept of developing an organizational “data culture” will gain prominence. Data and data analytics will continue to play key roles in global businesses of the future.

According to the article Why Data Culture Matters: “Organizational culture can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes.” Data culture being an integral part of the organizational culture can “neither be imported nor imposed.” It has to develop organically within an…
2019-09-17 07:35:00+00:00 Read the full story…
Weighted Interest Score: 3.2321, Raw Interest Score: 1.8194,
Positive Sentiment: 0.1440, Negative Sentiment 0.4450

The Lead up to Sibos: Entering the Second Generation of Connectivity

rconnected World’. In a 3-part series, we look at the power of AI, the value of Levering Data and the challenges and opportunities around regulation in Financial services. We set out to capture where Artificial Intelligence is impacting most, the concerns it raises and how the industry can use AI to maximum effect in the future. We ask participants about the importance of developing a data strategy, the problems leveraging data overcomes and the new & improved services it leads to. The final part to our series will look at Regulation and how the banks are adapting to today’s regulatory demands, we question who will …
2019-09-18 09:39:00 Read the full story…
Weighted Interest Score: 3.2105, Raw Interest Score: 1.6667,
Positive Sentiment: 0.5952, Negative Sentiment 0.7143

Banks prioritise digital standardisation and collaboration

rconnected World’. In a 3-part series, we look at the power of AI, the value of Levering Data and the challenges and opportunities around regulation in Financial services. We set out to capture where Artificial Intelligence is impacting most, the concerns it raises and how the industry can use AI to maximum effect in the future. We ask participants about the importance of developing a data strategy, the problems leveraging data overcomes and the new & improved services it leads to. The final part to our series will look at Regulation and how the banks are adapting to today’s regulatory demands, we question who will …
2019-09-18 16:05:00 Read the full story…
Weighted Interest Score: 3.2105, Raw Interest Score: 1.6667,
Positive Sentiment: 0.5952, Negative Sentiment 0.7143

Cloud Data Center Construction Boom Is Good News for Chip and Hardware Suppliers

While capital spending on the hardware going inside of cloud data centers has temporarily cooled this year, spending on data center construction still looks very strong.

Alphabet/Google (GOOGL) provided the latest evidence on Friday, when it announced that it’s spending €3 billion ($3.3 billion) to expand its European data center footprint over the next two years. The announcement comes seven months after Google said it would invest $13 billion …
2019-09-20 15:46:50-04:00 Read the full story…
Weighted Interest Score: 3.1331, Raw Interest Score: 1.6330,
Positive Sentiment: 0.2074, Negative Sentiment 0.0518

Big Data Career Notes: September 2019 Edition

In this monthly feature, we’ll keep you up-to-date on the latest career developments for individuals in the big data community. Whether it’s a promotion, new company hire, or even an accolade, we’ve got the details. Check in each month for an updated list and you may even come across someone you know, or better yet, yourself!

Archana Agrawal

MongoDB has announced that it has appointed Archana Argawal to the company’s board of directors. Agrawal is currently head of enterprise and cloud marketing for Atlassian…
2019-09-19 00:00:00 Read the full story…
Weighted Interest Score: 3.1021, Raw Interest Score: 1.4682,
Positive Sentiment: 0.5210, Negative Sentiment 0.0947

What’s Ahead in Big Data and Analytics

SPECIAL DBTA ROUNDTABLE WEBINAR THURSDAY, DECEMBER 12 – 11:00 am PT / 2:00 pm ET

From data lakes and the cloud, to machine learning and artificial intelligence, the world of big data and analytics continues to evolve rapidly. The demand for fast access to information through better self-service capabilities is growing. At the same time, the need for improved governance and security practices is also intensifying. In response, leading organizations are turning to innovative new technologies and strategies to reinforce their an…
2019-12-12 00:00:00 Read the full story…
Weighted Interest Score: 3.0952, Raw Interest Score: 1.8283,
Positive Sentiment: 0.7154, Negative Sentiment 0.1590

Broadridge Announces Data Control Solution Suite

ed to help financial organisations address the operational challenges of managing the data life cycle. The suite combines Broadridge’s award-winning reconciliation and matching solution with enhanced data analytics, together with industry-leading multi-bank connectivity and flexible financial messaging.

Recognising that data inconsistencies can shake confidence, impede growth and inject unnecessary risk and cost into businesses, Broadridge is providing a more holistic approach to achieving operational control over transaction data. Its Data Control technology and services enable firms to create powerful co…
2019-09-23 07:48:41+00:00 Read the full story…
Weighted Interest Score: 2.9632, Raw Interest Score: 1.5379,
Positive Sentiment: 0.4126, Negative Sentiment 0.3001

Rosslyn brings ‘big data’ to the forefront

• Provides data management and analytics services

• Services delivered through RAPid platform

• Cash generative in the year to 30 April 2019

What Rosslyn does

( ) provides data management and analytics services to businesses through RAPid, a platform that automatically extracts, aggregates, improves and organises data and documents for analysis.

The company also has a research arm, RAPid Labs, which works with both private sector organisatio…
2019-09-17 00:00:00 Read the full story…
Weighted Interest Score: 2.9135, Raw Interest Score: 1.6525,
Positive Sentiment: 0.1889, Negative Sentiment 0.0472

On the Origin of Business Insight in a Data-Rich World

Where does business insight come from? In what circumstances does it arise? Does it erupt spontaneously when a critical mass of data has been reached? Or does it only present itself after a methodical analysis has been conducted? These are questions worth asking now, as we find ourselves in the midst of an architectural shift from on-prem Hadoop to cloud-based systems, and witnessing the emergence of automated machine learning and deep learning s…
2019-09-18 00:00:00 Read the full story…
Weighted Interest Score: 2.8695, Raw Interest Score: 1.7740,
Positive Sentiment: 0.1862, Negative Sentiment 0.2744

BigQuery and Google Data Studio: visualizing without a code!

We’re in an age where there’s so much data and a shortage of analysts (and time) to sift through it all. So, tools become absolutely necessary. And these tools are evolving to empower less technical folks – like marketers – to analyze and visualize their own large data sets. In this post, we’ll walk you through using the Google stack – BigQuery, Cloud Storage, and Google Data Studio – to do just that.

Getting Started with BigQuery

BigQuery is a…
2019-09-20 07:56:23+00:00 Read the full story…
Weighted Interest Score: 2.7667, Raw Interest Score: 1.4790,
Positive Sentiment: 0.1392, Negative Sentiment 0.1044

Apple ‘Overton’: Automating Low-Code Machine Learning

Apple has struggled in recent years to establish a robust artificial intelligence (A.I.) practice. This partially stems from the company’s ironclad privacy policies—it’s more difficult to analyze datasets for insights when internal rules prevent the company from using every piece of user data it can vacuum up. Nonetheless, Apple’s newest projects show that it’s powering ahead anyway—including one platform that, if it’s ever released, could change…
2019-09-19 00:00:00 Read the full story…
Weighted Interest Score: 2.7267, Raw Interest Score: 1.5876,
Positive Sentiment: 0.1058, Negative Sentiment 0.1482

How Up-And-Coming Music Companies Use Big Data For Optimal Results

Big data has brought major changes to countless industries. Healthcare, finance, criminal justice, and manufacturing have all been touched by advances in big data. However, big data is also transforming other industries. The music industry is relying more on big data than ever.

Darren Heitner wrote a great article on Inc. About the way that big data is revolutionizing the industry. This is a great opport…
2019-09-15 18:39:06+00:00 Read the full story…
Weighted Interest Score: 2.7121, Raw Interest Score: 1.4423,
Positive Sentiment: 0.5577, Negative Sentiment 0.3269

Modern Data Warehousing: Enterprise Must-Haves

SPECIAL DBTA ROUNDTABLE WEBINAR TUESDAY, NOVEMBER 19 – 11:00 am PT / 2:00 pm ET

To fit into modern analytics ecosystems, legacy data warehouses must evolve—both architecturally and technologically—to deliver the agility, scalability and flexibility that business need to thrive in today’s data-driven economy. Alongside new architectural approaches, a variety of technologies have emerged as key ingredients of modern data warehousing, from data vir…
2019-11-19 00:00:00 Read the full story…
Weighted Interest Score: 2.6801, Raw Interest Score: 1.6779,
Positive Sentiment: 0.2517, Negative Sentiment 0.1678

BNY Mellon expands ESG analytics service

BNY Mellon has expanded the firm’s ESG Analytics offering by integrating fixed income scoring for corporate bonds.

BNY Mellon clients now have the ability to view environmental, social and governance (ESG) and United Nations Global Compact (GC) scores on equities and fixed income at the portfolio level versus relevant benchmarks over time. Clients also have the ability to view the ESG and GC scores at the company-level.

An extension of BNY Me…
2019-09-23 00:00:00 Read the full story…
Weighted Interest Score: 2.6695, Raw Interest Score: 2.0701,
Positive Sentiment: 0.1690, Negative Sentiment 0.0845

A 6 Step Field Guide for Building Machine Learning Projects

Have data and want to know how you can use machine learning with it? Read this.

This article focuses on data modelling. It assumes you have already collected data, and are looking to build a machine learning proof of concept with it. Let’s break down how you might approach it.

The specifics of these steps will be different for each project. But the principles within each remain similar.

Deployment is taking your set of instructions and using it in an a…
2019-09-21 13:26:15.979000+00:00 Read the full story…
Weighted Interest Score: 2.6528, Raw Interest Score: 1.5347,
Positive Sentiment: 0.2457, Negative Sentiment 0.4028

Mindbreeze recognized once again as a Leader in the 2019 Gartner Magic Quadrant for Insight Engines

s of vision and ability to execute

LINZ, Austria–(BUSINESS WIRE)–#artificialintelligence–Mindbreeze, a leading global provider of appliances and cloud services for information insight and applied artificial intelligence with a focus on knowledge management for international companies, announced today that the company has been positioned by Gartner, Inc. as a Leader in the 2019 Magic Quadrant for Insight Engines.

A complimentary copy of the report can be accessed from the Mindbreeze website

“Mindbreeze enables our customers and their employees to garner and leverage crucial insights from their data. We work dir…
2019-09-20 00:00:00 Read the full story…
Weighted Interest Score: 2.6379, Raw Interest Score: 1.5994,
Positive Sentiment: 0.3998, Negative Sentiment 0.1200

AI learns the language of chemistry to predict how to make medicines

University of Cambridge researchers have shown that an algorithm can predict the outcomes of complex chemical reactions with over 90% accuracy, outperforming trained chemists. The algorithm also shows chemists how to make target compounds, providing the chemical ‘map’ to the desired destination. The results are reported in two studies in the journals ACS Central Science and Chemical Communications.

A central challenge in drug discovery and mater…
2019-09-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5913, Raw Interest Score: 1.2020,
Positive Sentiment: 0.1885, Negative Sentiment 0.2593

The AI arms race spawns new hardware architectures

As society turns to artificial intelligence to solve problems across ever more domains, we’re seeing an arms race to create specialized hardware that can run deep learning models at higher speeds and lower power consumption.

Some recent breakthroughs in this race include new chip architectures that perform computations in ways that are fundamentally different from what we’ve seen before. Looking at their capabilities gives us an idea of t…
2019-09-21 00:00:00 Read the full story…
Weighted Interest Score: 2.5889, Raw Interest Score: 1.5369,
Positive Sentiment: 0.1002, Negative Sentiment 0.1671

How AI for Earth is inspiring new generations to help the planet

with Dr. Robert Long of Seattle’s Woodland Park Zoo to develop an AI tool that processes data from wildlife camera traps to monitor species in the Pacific Northwest and in the Rocky Mountains. Using machine learning, this resource will be able to identify and index a wide variety of animals in a much shorter timeframe than if processed manually. Camera traps can generate large amounts of data, some of which are false positives – for example, when something triggers the camera, but nothing meaningful is photographed. This AI tool examines the images and eliminates images that don’t require more detailed inspe…
2019-09-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5793, Raw Interest Score: 1.2267,
Positive Sentiment: 0.2115, Negative Sentiment 0.1481

Splunk Announces New Platform Initiatives

Splunk, a provider of the data-to-everything platform, is making several advancements to pricing, partner, and investment initiatives designed to help customers make smarter business decisions.

“We are living in a time of unprecedented change. The volume of data continues to grow at exponential rates, creating massive opportunities for those that are able to leverage this vast resource. Yet, most data is trapped inside an organization’s devices,…
2019-09-19 00:00:00 Read the full story…
Weighted Interest Score: 2.5541, Raw Interest Score: 1.3636,
Positive Sentiment: 0.2814, Negative Sentiment 0.0866

ASX set to open flat on trade tensions

“In our view, a rate cut is now likely in October as reflected in the Reserve Bank’s reassessment of the global and domestic outlook in the September Board minutes,” Ms Owyong said in a week ahead note. “Importantly, the minutes dropped the reference to waiting for an accumulation of evidence before considering whether to cut rates and suggested that the bank has downgraded its central scenario for the economy.”

The RBA “looks likely to downgrad…
2019-09-21 00:00:00 Read the full story…
Weighted Interest Score: 2.5284, Raw Interest Score: 1.2536,
Positive Sentiment: 0.1025, Negative Sentiment 0.4100

Dremio Noses Into Cloud Lakes with Analytics Speedup

Most of today’s big data action is occurring in the cloud, where companies are building massive data lakes atop object storage systems like AWS S3 and Microsoft ADLS. While object stores offer tremendous scalability, they’re notoriously slow. Those who are tired with slow responses may want to check out the latest from Dremio, which today unveiled some innovative ways to speed SQL queries on the cloud.

The original desi…
2019-09-17 00:00:00 Read the full story…
Weighted Interest Score: 2.4615, Raw Interest Score: 1.5839,
Positive Sentiment: 0.1070, Negative Sentiment 0.1070

Mathematicians Top List of Hottest Job Titles Yet Again

Mathematicians and data engineers remain some of the hottest job titles among employers, according to a new breakdown of data from Burning Glass’s NOVA platform, which analyzes millions of active job postings.

That shouldn’t come as a shock to anyone who monitors NOVA’s data; mathematicians placed in the top spot last month, too, followed by data engineers and actuaries. That job postings for mathematicians grew 73 percent in September—on top of…
2019-09-20 00:00:00 Read the full story…
Weighted Interest Score: 2.4457, Raw Interest Score: 1.5873,
Positive Sentiment: 0.1361, Negative Sentiment 0.0907

Open Banking Scares Consumers, But They Want What APIs Can Deliver

Banks and credit unions increasingly grasp the importance of open banking, but the term is not at all understood by consumers, especially in the U.S. Yet people want easier ways to manage their money and that often involves the use of third-party apps that access consumer financial data. The potential of open banking won’t be reached without efforts to educate consumers on its benefits.

“Open banking” is a simple term, but its meanings range all…
2019-09-18 00:04:40+00:00 Read the full story…
Weighted Interest Score: 2.4208, Raw Interest Score: 1.3895,
Positive Sentiment: 0.1684, Negative Sentiment 0.1158

Treasury Trading Q&A: Josh Holden, OpenDoor

What is the state of transaction cost analysis in the U.S. Treasuries market? Markets Media caught up with Josh Holden, Chief Information Officer at OpenDoor Securities, to discuss.

What structural issues in U.S. Treasuries have created a heightened demand for better TCA tools?

Treasuries has always been a dealer-centric market. But post-crisis, dealers have been allocating less balance sheet to off-the-runs and TIPs. There’s less willingness t…
2019-09-20 19:10:12+00:00 Read the full story…
Weighted Interest Score: 2.4096, Raw Interest Score: 1.1115,
Positive Sentiment: 0.3644, Negative Sentiment 0.1458

Database, Data Management Upgrades Keep Coming

Data analytics and database vendors vendor continue to churn out new versions of their platforms that integrate new features like cloud-native functionality and more granular views of structured and unstructured data. The latter is intended to help manage soaring data volumes in hopes of ensuring analysts that they can trust data.

Two more turned up this week: Tableau Software released expanded data and server…
2019-09-18 00:00:00 Read the full story…
Weighted Interest Score: 2.4076, Raw Interest Score: 1.5259,
Positive Sentiment: 0.1356, Negative Sentiment 0.0678

Buzzy insurtechs have raised $3 billion already this year and are touting AI and big data. But the tech could change how policies are written, pricing out risky customers.

w tech in the insurance space may end up meaning those most in need of help get left behind.

Startups blending insurance and technology have been boasting that their use of a wider range of data and artificial intelligence-based tools is changing the way the entire industry works, with many hinting it could eventually lead to better underwriting and pricing.

And while that may help the expansion of insurance products into more niche areas, some are sounding the alarm about the possibility that pricing will become too sophisticated. Coverage that is more tailored to customers’ needs could result in those carrying t…
2019-09-23 00:00:00 Read the full story…
Weighted Interest Score: 2.3248, Raw Interest Score: 1.1468,
Positive Sentiment: 0.1578, Negative Sentiment 0.2209

Tamr Launches Fall 2019 Data Unification System to Power Breakthrough Analytic Insights

ase, “Tamr, Inc. announced today the general availability of the Fall 2019 release of the company’s patented data unification system. Tamr is a data integration software platform that uses supervised machine learning to unify data silos. It enables data engineers (who aren’t data scientists) to harness the power of machine learning to build automated pipelines that integrate, master, and classify disparate, dirty data. With the Fall 2019 release, Tamr offers cloud support, geospatial mapping and additional enhancements to make it faster and easier to unify large numbers of heterogeneous sources.”

The release…
2019-09-20 07:10:12+00:00 Read the full story…
Weighted Interest Score: 2.2818, Raw Interest Score: 1.7172,
Positive Sentiment: 0.4007, Negative Sentiment 0.0572

Sounding Out Car Noises and AI Autonomous Cars

By Lance Eliot, the AI Trends Insider

[Ed. Note: For reader’s interested in Dr. Eliot’s ongoing business analyses about the advent of self-driving cars, see his online Forbes column: https://forbes.com/sites/lanceeliot/]

The sounds of silence.

You might have thought that I was referring to the famous song by Simon and Garfunkel, but I am actually referring to the moments in which silence is golden. In particular, I’m referring to cars that are…
2019-09-17 11:58:02+00:00 Read the full story…
Weighted Interest Score: 2.2690, Raw Interest Score: 0.6900,
Positive Sentiment: 0.0638, Negative Sentiment 0.2505

WANdisco Releases the LiveAnalytics Platform

WANdisco, the LiveData company, is releasing the LiveAnalytics platform, ensuring uninterrupted business insights by migrating data from on-premises Hadoop environments into Spark-based analytics in the cloud, such as Databricks.

LiveAnalytics allows both migrated and migrating data to be immediately and continuously available for analysis.

LiveAnalytics works in tandem with WANdisco’s LiveMigrator, its petabyte-scale, non-blocking, single scan…
2019-09-20 00:00:00 Read the full story…
Weighted Interest Score: 2.2563, Raw Interest Score: 1.4892,
Positive Sentiment: 0.1805, Negative Sentiment 0.1354

Red Hat OpenStack Platform 15 Enhances Infrastructure Security and Cloud-Native Integration

According to a recent press release, “Red Hat, Inc., the world’s leading provider of open source solutions, today announced the general availability of Red Hat OpenStack Platform 15, the latest version of its highly scalable and agile cloud Infrastructure-as-a-Service (IaaS) solution. Based on the OpenStack community’s “Stein” release, Red Hat OpenStack Platform 15 adds performance and cloud security enhancements and expands the platform’s ecosys…
2019-09-23 07:05:02+00:00 Read the full story…
Weighted Interest Score: 2.2438, Raw Interest Score: 1.6343,
Positive Sentiment: 0.8172, Negative Sentiment 0.0511

Data Startup Aims to Make S3 ‘Work Like Dropbox’

Quilt Data emerged from stealth today with a new service that aims to make S3 work more like Dropbox, the handy file sharing service. For about $500 per month, Quilt Data allows teams to securely large share files that are too big to distribute via FTP or Web archives, and simultaneously get visibility into the contents of the file through its preview feature.

Quilt Data‘s two founders, Aneesh Karve and Kevin Moore, met while studying in the gra…
2019-09-19 00:00:00 Read the full story…
Weighted Interest Score: 2.2354, Raw Interest Score: 1.4909,
Positive Sentiment: 0.1316, Negative Sentiment 0.0877

Tealium Launches Built-In Machine Learning Tech for the Customer Data Platform

Tealium this week announced a built-in machine learning technology for Tealium AudienceStream, its market-leading Customer Data Platform (CDP).

The company says its service offers machine learning insights across the entire tech stack through the creation of more intelligent audiences.

With Tealium Predict, organizations can automatically draw conclusions about what customers are likely to do in the future and design tailored programs that directly …
2019-09-20 16:50:52+10:00 Read the full story…
Weighted Interest Score: 2.2351, Raw Interest Score: 2.0921,
Positive Sentiment: 0.2510, Negative Sentiment 0.1255

How AI Can Champion Cybersecurity in the Insurance Industry and Beyond

ajor data leaks from high profile companies like Equifax set a clear message that even big players are vulnerable to security breaches – and companies in industries including insurance are turning to artificial intelligence (AI) to secure their sensitive data.

It is imperative that companies across all industries – especially when dealing with the personal data of consumers – work to avoid data breaches or liabilities when it comes to user information. Let’s delve into the top data security considerations for insurance companies and explore how AI can help protect enterprises of all sizes.

The Ever-Changing Cybers…
2019-09-18 11:00:00+00:00 Read the full story…
Weighted Interest Score: 2.1929, Raw Interest Score: 0.9704,
Positive Sentiment: 0.1820, Negative Sentiment 0.5701

Oktoberfest : Quick analysis using Pandas, Matplotlib, and Plotly

Oktoberfest 2019 has started! Oktoberfest is the world’s largest beer festival and is held annually in Munich since 1810. It lasts between 16 and 18, running from mid or late September to the first Sunday in October, with more than 6 million visitors every year. 🍺 🍺

Munchen.de is the official portal of the city of Munich with contains more than 140 datasets, covering a wide rage of topics such as economy, transport, tourism, or culture. Currentl…
2019-09-22 14:38:02.362000+00:00 Read the full story…
Weighted Interest Score: 2.1717, Raw Interest Score: 0.9716,
Positive Sentiment: 0.1000, Negative Sentiment 0.1000


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