IBM Big Data Hub

AUGUST 9, 2023

Why phishing simulations are important Recent statistics show phishing threats continue to rise. Since 2019, the number of phishing attacks has grown by 150% percent per year— with the Anti-Phishing Working Group (APWG) reporting an all-time high for phishing in 2022 , logging more than 4.7 million phishing sites.

Testing 74

Testing Measurement Behavioral Analytics Reporting 74

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 97

Advertising Cost-Benefit ROI Sales 97

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. ” The Atlantic – Workers Love AirPods Because Employers Stole Their Walls , Amanda Mull, April 2019. Here we come back to the upward trend in searches for Data Science.

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

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. Do those concerns sound familiar?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

O'Reilly on Data

MARCH 20, 2019

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. An attacker could use an adversarial example attack to grant themselves a large loan or a low insurance premium or to avoid denial of parole based on a high criminal risk score. Newer types of fair and private models (e.g.,

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

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

Domino Data Lab

MAY 8, 2019

That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Given how so much of IT gets driven by concerns about risks and costs, in practice auditability tops the list for many business stakeholders. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). Ben and I also wrote articles for each of the surveys, summarizing the highlights.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

datapine

FEBRUARY 23, 2023

2) Charts And Graphs Categories 3) 20 Different Types Of Graphs And Charts 4) How To Choose The Right Chart Type Data and statistics are all around us. That is because graphical representations of data make it easier to convey important information to different audiences. Table of Contents 1) What Are Graphs And Charts?

Visualization 177

Visualization Dashboards Sales Measurement 177

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

O'Reilly on Data

MAY 21, 2019

Thus, many developers will need to curate data, train models, and analyze the results of models. With that said, we are still in a highly empirical era for ML: we need big data, big models, and big compute. A typical data pipeline for machine learning. Managing risk in machine learning”.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

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 102

ROI Statistics Machine Learning Measurement 102

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. 2019 was a particularly major year for the business intelligence industry. Suddenly advanced analytics wasn’t just for the analysts.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

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. As we mentioned in our business intelligence buzzwords article for 2019 , mobile usage is becoming an increasing factor in BI.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

O'Reilly on Data

JANUARY 25, 2021

Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Let’s look at the data, starting at the highest level: O’Reilly online learning itself. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019. Observability” risks becoming the new name for monitoring.

Machine Learning 363

Machine Learning Software Testing Technology 363

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

Jet Global

MAY 1, 2023

CEO Priorities Grow revenue and “hit the number” Manage costs and meet profitability goals Attract and retain talent Innovate and out-perform the competition Manage risk Connect the Dots Present embedded analytics as a way to differentiate from the competition and increase revenue. Present your business case.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52