AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Metadata 99

Metadata Modeling Data Processing Unstructured Data 99

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform. End-to-end Data Lifecycle.

Risk 88

Risk Marketing Technology Management 88

Jedox

OCTOBER 8, 2020

We had the Financial Crisis/Recession of 2008, where hopefully the comment “Well that will never happen” has been struck from our lexicon and is now considered a punishable capital offense. The 2008 economic crisis was a watershed event for FP&A teams and scenario planning.

Uncertainty 75

Uncertainty Cost-Benefit Unstructured Data Data-driven 75

Cloudera

DECEMBER 9, 2021

Their use of Cloudera technology provides a model for others to follow as they embark on their own data-driven transformative journeys. MTN leveraged a data lake powered by the EVA (Enterprise Value Analytics) platform and deployed Cloudera CDP to unify data access across its operations. …and congratulations to the winner: MTN .

Data Lake 84

Data Lake Data-driven Finance Machine Learning 84

AWS Big Data

JUNE 2, 2023

My team supports analytics throughout BWH Hotels, including some affiliate and international organizations. Migrating to AWS and QuickSight After a six-month proof of concept, we decided to move fully to AWS for our data and analytics needs. Having used Cognos since 2008, this was not just a lift-and-shift migration.

Business Intelligence 52

Business Intelligence Enterprise Dashboards Sales 52

Jen Stirrup

OCTOBER 30, 2022

These propensity models are useful for understanding which customers are most likely to purchase a given set of products. This model can assist in decision making and in focusing marketing efforts. As a first step to customer insight, analytical tools can summarise and aggregate historical information about customers.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

Cloudera

JANUARY 26, 2022

In 1991, the World Wide Web (WWW) launched, and distributed computing in the form of the client-server model started to take shape. In 2008, Cloudera was born. The amount of data being collected grew, and the first data warehouses were developed. Big Data” became a topic of conversations and the term “Cloud” was coined. .

Data Processing 85

Data Processing IoT Cost-Benefit Digital Transformation 85

Cloudera

MARCH 18, 2021

FRTB is designed to address some fundamental weaknesses that did not get addressed in the post-2008 financial crisis regulatory reforms. A revised internal models approach (IMA) combined with an overhaul of the standardized approach (SA). Complete audit trail(s) for data, models, and risk calculations. .

Risk 55

Risk Machine Learning Risk Management Measurement 55

Smart Data Collective

APRIL 5, 2022

Here at Smart Data Collective, we never cease to be amazed about the advances in data analytics. We have been publishing content on data analytics since 2008, but surprising new discoveries in big data are still made every year. One of the biggest trends shaping the future of data analytics is drone surveying.

Data Collection 107

Data Collection Data Quality Big Data Data-driven 107

Cloudera

JUNE 23, 2021

Evolving your analytics and risk models to accommodate climate change inputs and regulations beyond weather-related natural disasters is increasingly important. Insurers will have to adjust their models frequently to match local markets. . Data and Analytics Can Help . Rigorous updates to models.

Insurance 52

Insurance Risk Modeling Risk Management 52

Ontotext

DECEMBER 30, 2022

In 2008, we received a small round of funding and focused on bringing this technology to the market. SNB is the most comprehensive benchmark for graph analytics and was previously targeted at labeled property graph (LPG) engines. However, developing these models from scratch for each and every solution can be slow, expensive and risky.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Ontotext

DECEMBER 30, 2022

In 2008, we received a small round of funding and focused on bringing this technology to the market. SNB is the most comprehensive benchmark for graph analytics and was previously targeted at labeled property graph (LPG) engines. Typical memory usage is now 15% to 20% less. Global Sales planning.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

DataKitchen

MAY 10, 2021

When analytics and dashboards are inaccurate, business leaders may not be able to solve problems and pursue opportunities. If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics. Data errors impact decision-making.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Jet Global

MARCH 5, 2019

AI, colloquially, is used to refer to a number of computer-powered business decision drivers, including automation (not AI), data modeling (not AI), and reporting and analytics (also not AI). Analytics and reporting: Capturing, structuring, and storing data is good—but being able to analyze and report on it is the ultimate end goal.

Business Intelligence 75

Business Intelligence OLAP Visualization Reporting 75

CDW Research Hub

MAY 24, 2019

Consumption models in a cloud environment—specifically Azure—are becoming more desirable as the adoption of cloud technology progresses. Monitoring capabilities can be quickly updated to report, alert and log the day-to-day activities of the platform and leverage the operational model currently in place within your organization.

Data Processing 40

Data Processing Management Modeling Strategy 40

Cloudera

JANUARY 3, 2019

Our pre-merger customer bases have very little overlap, giving us a considerable enterprise installed base whose demand for IoT, analytics, data warehousing, and machine learning continues to grow. Our bet in 2008 has proven prescient. I can’t think of a comparable enterprise software transaction in my thirty years in the industry.

IoT 74

IoT Machine Learning Data Warehouse Enterprise 74

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 83

Data Warehouse Sales Visualization Data Processing 83

Paul Blogs on BI

MARCH 25, 2020

Some universities and institutions have built out predictive models based on this data which are even more likely to be erroneous. Some of the best BI solutions I have seen have been in the area of spend analytics. If that data analysis is based on missing or bad data, then actions taken on it are likely to be flawed.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

Sisense

JULY 14, 2019

You also want to choose ISO-compliant analytics software and cloud database partners. Whatever platform you choose should also allow admins to easily manage security settings and user access from one place and give them usage analytics to determine who’s doing what with the system and make sure that no one is misusing their access.

Software 75

Software Strategy Data Warehouse Modeling 75

bridgei2i

MAY 26, 2020

In the post-COVID era, they can be empowered with a high standard of data and analytics sophistication to cope and thrive. To introduce him better, he has been a supply chain analytics professional for over 14 years. And the third dimension is their data and analytics sophistication. Subscribe Now. Transcript. Anushruti: Right.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

CIO Business Intelligence

FEBRUARY 27, 2023

When Greg Greenlee joined the IT industry in 2008, the lack of representation of Black IT professionals among attendees and speakers at tech conferences and events was readily apparent. “It Students learn at their own pace and can complete a nanodegree program tailored to help land a high-paying career in tech.

Technology 103

Technology Data Processing IT Interactive 103

AWS Big Data

APRIL 28, 2023

This is the second post of a three-part series detailing how Novo Nordisk , a large pharmaceutical enterprise, partnered with AWS Professional Services to build a scalable and secure data and analytics platform. The workflow steps are as follows: A user authenticates on an IdP used by the analytics tool that they are trying to access.

Data Governance 65

Data Governance Management Data-driven Data Lake 65

Data Science and Beyond

JULY 22, 2018

Kaggle was only about predictive modelling competitions back then, and so I believed that data science is about using machine learning to build models and deploy them as part of various applications. It is now much easier to deploy machine learning models, even without a deep understanding of how they work.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

datapine

NOVEMBER 19, 2019

Visual analytics: Around three million images are uploaded to social media every single day. In business intelligence, we are evolving from static reports on what has already happened to proactive analytics with a live dashboard assisting businesses with more accurate reporting.

Technology 279

Technology Internet of Things IT IoT 279

Occam's Razor

SEPTEMBER 29, 2009

See if you were able to get more traffic to arrive at your site, and if they were Existing Visitors or New Visitors (hopefully measured with a first party cookie in your website analytics tool). Bonus reading material: Multichannel Analytics: Tracking Offline Conversions. Web Analytics. 7 Best Practices ].

Measurement 128

Measurement Metrics Analytics Marketing 128

Sisense

APRIL 2, 2019

It’s also shaping the way BI and Analytics are deployed. The DevOps movement started to come together sometime between 2007 and 2008. This is when IT operations and software development communities started to talk about problems in the software industry, specifically around the traditional software development model.

Software 80

Software Testing Enterprise IT 80

AWS Big Data

APRIL 25, 2023

We have used an AWS Glue job for the ETL pipeline to showcase how you can use purpose-built analytics service for complex ETL needs. Summary In this post, we showed how you can support a cross-account model to exchange data between different partners with different SaaS integrations using Amazon AppFlow.

Sales 74

Sales Visualization Software Marketing 74

Domino Data Lab

SEPTEMBER 18, 2019

Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Plotly also has an open-source Python framework called Dash that can be used for building analytical web applications. Introduction. In Figure 10.4,

Visualization 99

Visualization Interactive Machine Learning Data Science 99

Occam's Razor

OCTOBER 14, 2014

See step four in the process for creating your Digital Marketing and Measurement Model.]. If you've read my first book Web Analytics: An Hour A Day, you know that I've advocated this strategy since 2008! There are four reasons, again from Web Analytics: An Hour A Day, from 2008 (!): See Page 269. :).

Key Performance Indicator 133

Key Performance Indicator Metrics Reporting Marketing 133

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. 2008: Microsoft announces Windows Azure (PaaS) with Azure Blob storage (S3 competitor). AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Ontotext

JANUARY 21, 2021

Even if you have detailed models of your business, data and the technology artifacts that support the business, ontology alignment is still an active area of research with few, if any, off the shelf tools to support such an effort. This is a nontrivial task. Historical Context. From these humble beginnings grew the OWL representation.

Modeling 72

Modeling Finance Technology Insurance 72

Occam's Razor

NOVEMBER 18, 2014

Ok, so perhaps as the author of two bestselling books on analytics I love it a little bit more! In each case the creator did something interesting that made me wonder how I can use their strategy in my daily efforts in service of digital marketing and analytics. Short story #2: Predictive Modeling, Quantifying Cost of Inaction.

Visualization 143

Visualization Slice and Dice Predictive Modeling Metrics 143

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Sources of model risk. Model risk management. Image by Ben Lorica.

Machine Learning 37

Machine Learning Management Enterprise Risk Management 37

Domino Data Lab

AUGUST 8, 2019

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists. 2008 – Financial crisis : scientists flee Wall St.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

bridgei2i

AUGUST 11, 2020

In our AI to Impact podcast, we’ve been talking with the AI & Analytics leaders, digital transformation advisors, as well as BRIDGEi2i business leaders to understand their point of view on the current situation and its impact on various industries and how enterprises can maintain business continuity while building resilience.

Sales 98

Sales Enterprise B2B Digital Transformation 98

Domino Data Lab

JULY 22, 2019

how “the business executives who are seeing the value of data science and being model-informed, they are the ones who are doubling down on their bets now, and they’re investing a lot more money.” Predictive analytics, yeah, not so much.” Those workflows would feedback into your business analytics. Transcript.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

MARCH 22, 2022

Fractal Analytics has appointed Manish Tiwari as its CIO. He is expected to strengthen the company’s cloud solution portfolio, deliver an enhanced cloud experience for customers, and develop industry-specific solutions available on IaaS, PaaS, and SaaS models. December 2021. Airtel CISO Manish Tiwari joins Fractal as CIO.

Internet Publishing and Broadcasting 98

Internet Publishing and Broadcasting Digital Transformation Insurance Recreation/Entertainment 98