Cloudera

JANUARY 22, 2019

In conjunction with the evolving data ecosystem are demands by business for reliable, trustworthy, up-to-date data to enable real-time actionable insights. Big Data Fabric has emerged in response to modern data ecosystem challenges facing today’s enterprises. What is Big Data Fabric? Data access.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Smart Data Collective

JUNE 3, 2021

The market for data analytics in the insurance sector is projected to be worth nearly $22.5 Many of the applications of big data for insurance companies will be realized with machine learning technology. If a customer has already filed multiple complaints with the insurer, it could mean they are at risk of churn.

Insurance 98

Insurance Machine Learning Cost-Benefit Risk 98

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 82

Analytics Insurance Big Data Uncertainty 82

Smart Data Collective

JUNE 10, 2019

When you consolidate log data like this, it is easier to manage and analyze it, allowing you to identify patterns and trends from different log data points of origin and also mitigating the risk of losing that data in a production environment that is scaling all of the time automatically.

Analytics 74

Analytics Strategy Statistics Data Processing 74

AWS Big Data

FEBRUARY 1, 2024

Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. We also used FactSet’s market data solutions for historical and streaming market quotes and trades.

Data Warehouse 123

Data Warehouse Dashboards Risk Management Risk 123

TDAN

DECEMBER 31, 2019

If you are targeted by a criminal online, then you risk losing everything— from your essential data to your reputation. The average cost of a global data breach cost has increased in 2019 and is now $3.92 Cyber-attacks are a huge problem for today’s businesses.

Risk 69

Risk Risk Management Data Architecture Data Strategy 69

datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Risk Management (most likely within context of governance).

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Domino Data Lab

JUNE 2, 2019

She had much to say to leaders of data science teams, coming from perspectives of data engineering at scale. And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Ludwig (@RandiRLudwig) May 23, 2019.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Smart Data Collective

JANUARY 14, 2021

In 2019, Forbes published an article showing that machine learning can increase productivity of the financial services industry by $140 billion. While this obviously means that there is more risk, it also gives more informed investors a chance to beat market benchmarks. Every individual investor has their own set of objectives.

Predictive Analytics 81

Predictive Analytics Forecasting Analytics Machine Learning 81

Smart Data Collective

JUNE 15, 2022

One of the secrets to attracting and retaining customers is to become more data-centric. trillion in 2019? According to many surveys, more than 90% of retail organizations across a wide range of sectors feel location data is crucial to their success. The retail industry is expanding all the time.

Advertising 98

Advertising Cost-Benefit ROI Sales 98

Sisense

JULY 29, 2020

In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data. If they don’t, they risk failure and can jeopardize their survival.

Analytics 95

Analytics Digital Transformation Data-driven Sales 95

Domino Data Lab

AUGUST 8, 2019

Sci Foo 2019. Data science teams should watch what’s happening here, especially the emphasis in the EU. For example, meeting Carole Goble was one of the top highlights of Sci Foo 2019 for me. The probabilistic nature changes the risks and process required. Data governance, for the win!

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

CIO Business Intelligence

MAY 24, 2022

Cloud is becoming an increasing popular option for organisations to store data to power data analytics and business intelligence functions: data that is growing rapidly in volume and variety. However migrating data to the cloud and managing it in the cloud creates multiple challenges. 1. data breaches.

Management 71

Management Risk Big Data Enterprise 71

Domino Data Lab

OCTOBER 9, 2019

In some cases, their work is vital when millions of lives may be at risk due to natural disasters. In other cases, their work comes under intense political scrutiny, often targeting the veracity of data—e.g., Monica Youngman, director of data stewardship—check out her slides for the “Data Archiving at NOAA” keynote.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Andrew White

APRIL 22, 2020

Many highly leveraged firms will be at risk; debt will be at record levels in public and private so anyone who has cash will be predatory. Data, analytics and AI. For years aggregated economic data from OECD and US BEA suggested that productivity had been on a go-slow for some time. Big data; small data.

Software 52

Software Uncertainty Measurement Marketing 52

Smart Data Collective

OCTOBER 14, 2019

.” Doing this protects the privacy of the people involved by ensuring that a malicious person could not trace a data source back to a single individual or otherwise reveal their identity. In September 2019, Google decided to make it’s Differential Privacy Library available as an open-source tool. Kubernetes.

Data Science 67

Data Science Machine Learning Big Data Interactive 67

Jet Global

MAY 1, 2023

Positioning Embedded Analytics for Each Executive Here are some tips on understanding executives’ priorities and getting them on board with the project. Show how embedded analytics will enhance sales and marketing through better demos and shorter sales cycles. Present your business case.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Smart Data Collective

JUNE 26, 2019

More specifically, having an excessive amount of dark data could mean you spend more time searching for data than analyzing it. Or, dark data could open your company to regulatory risks if you cannot retrieve requested information during an audit. Pay Attention to Data Stored on Mobiles and in the Public Cloud.

ROI 103

ROI Statistics Machine Learning Measurement 103