AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Data Lake 66

Data Lake Cost-Benefit Dashboards Data Warehouse 66

Smart Data Collective

APRIL 24, 2020

Perhaps one of the biggest perks is scalability, which simply means that with good data lake ingestion a small business can begin to handle bigger data numbers. The reality is businesses that are collecting data will likely be doing so on several levels. Proper Scalability. Stores in Raw Format. Uses Powerful Algorithms.

Data Lake 99

Data Lake Data Collection Deep Learning Management 99

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 340

Data Science Data Lake Data mining Deep Learning 340

Smart Data Collective

APRIL 2, 2019

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

Data Lake 83

Data Lake Big Data OLAP Testing 83

Sisense

DECEMBER 23, 2019

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Get money out of your data. It should also be able to handle live datasets that constantly update and allow you to mash them up with cached data.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

O'Reilly on Data

FEBRUARY 19, 2021

The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. A Wave of Cloud-Native, Distributed Data Frameworks.

Data Lake 289

Data Lake Data Warehouse Machine Learning Modeling 289

Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 76

Data Lake Data Governance Cost-Benefit Machine Learning 76

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 119

Data Integration Data Lake Metadata Data Warehouse 119

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Despite being primarily an AWS shop, Rocket has taken a model-agnostic approach to generative AI platforms.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

CIO Business Intelligence

AUGUST 4, 2022

That’s typically due to the exponential growth in dataset size and complexity of AI models. “In In an early phase, you might submit a job to the cloud where a training run would execute and the AI model would converge quickly,” says Tony Paikeday, senior director of AI systems at NVIDIA.

Modeling 97

Modeling Cost-Benefit ROI Data Lake 97

IBM Big Data Hub

JUNE 14, 2023

And then you need highly specialized, expensive and difficult to find skills to work the magic of training an AI model. But that’s all changing thanks to pre-trained, open source foundation models. This is usually text, but it can also be code, IT events, time series, geospatial data, or even molecules.

Modeling 95

Modeling Data Lake Enterprise Deep Learning 95

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 79

Risk Modeling Management Metadata 79

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

CIO Business Intelligence

APRIL 1, 2024

Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. You’ll also institute guardrails for data governance, data quality, data integrity, and data security.

Data Lake 142

Data Lake Consulting Uncertainty Risk 142

IBM Big Data Hub

APRIL 15, 2024

Or we create a data lake, which quickly degenerates to a data swamp. Additionally, these accelerators are pre-integrated with various cloud AI services and recommend the best LLM (large language model) for their domain. Generative AI can create foundation models for assets.

Manufacturing 105

Manufacturing Contextual Data Knowledge Discovery Data Lake 105

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 89

Data Lake Snapshot Big Data Data-driven 89

Andrew White

DECEMBER 2, 2022

On the third day of Christmas my CIO said to me, three AI models, two industry clouds, and a budget in and on time. On the fourth day of Christmas my CIO said to me, four data hubs, three AI models, two industry clouds, and a budget in and on time.

Data Lake 59

Data Lake Dashboards Modeling Analytics 59

erwin

JUNE 7, 2022

Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Data modeling for the cloud: good database design means “right size” and savings. Figure 1: Pricing for a 4 TB data warehouse in AWS. Data Modeling. So, let go of any old OLTP design.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Choose Create endpoint.

Data Lake 93

Data Lake Data Warehouse Testing Business Objectives 93

KDnuggets

JANUARY 18, 2023

7 Best Platforms to Practice SQL • Explainable AI: 10 Python Libraries for Demystifying Your Model's Decisions • ChatGPT: Everything You Need to Know • Data Lakes and SQL: A Match Made in Data Heaven • Google Data Analytics Certification Review for 2023

Data Lake 84

Data Lake Modeling Data Analytics Analytics 84

AWS Big Data

MARCH 21, 2024

You want real-time access to this data so you can monitor performance in real time, and detect and mitigate issues quickly. You also need longer-term access to this data for machine learning (ML) models to run predictive maintenance assessments, find optimization opportunities, and forecast demand.

Data Lake 92

Data Lake Management Modeling Optimization 92

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

Data Quality 87

Data Quality Data Governance Data Lake Testing 87

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

CDW Research Hub

JULY 18, 2022

One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models. Security Data Lake. Learn more about our Security Data Lake Solution.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

AWS Big Data

NOVEMBER 10, 2023

As a result of utilizing the Amazon Redshift integration for Apache Spark, developer productivity increased by a factor of 10, feature generation pipelines were streamlined, and data duplication reduced to zero. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. options(**read_config).option("query",

Data Processing 89

Data Processing Data Lake Data Warehouse Optimization 89

CIO Business Intelligence

DECEMBER 6, 2023

Enabling consistency in the data sets from these varied sites is integral to DS Smith’s analytics strategy, as well as for anticipated changes in the company’s technology and business models, Dickson says. Here, Dickson sees data generated from its industrial machines being very productive.

Manufacturing 97

Manufacturing Data Lake Digital Transformation Machine Learning 97

CIO Business Intelligence

JULY 26, 2023

Joe Wilhemy, vice president of Re/Max’s business technology and data platforms, says Re/Max has built several machine learning models and adopted one via an acquisition called “first mover score,” which is designed to inform an agent about contacts in their database who are most likely to list their homes in the near future.

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

Ontotext

APRIL 10, 2024

Data Lakes, Data Catalogs, and Findability Organizations approach data lakes as cheap storage. They move data to data lakes creating another copy – the mantra being – “ Lets move the data to a data lake and then we will figure out what to do with it”.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Timo Elliott

APRIL 1, 2023

It’s not creating the models or doing the data science—it’s actually making it part of an operational process. Data scientists typically extract data from operational systems and move it to a hyperscalar data lake, then use open source algorithms to create and test their mdoels.

Data Lake 101

Data Lake Testing Data Science Modeling 101

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.” ” Watsonx.ai ” Watsonx.ai

Management 89

Management IT Machine Learning Metrics 89

CIO Business Intelligence

MARCH 18, 2024

By leveraging data replication and synchronization, businesses can effectively integrate vast amounts of fragmented data from a variety of environments into a more cohesive data experience for its users. That data also only needs to be replicated once and can then subsequently be applied to multiple targets.

Cost-Benefit 98

Cost-Benefit Data Lake Machine Learning Data Integration 98

IBM Big Data Hub

MAY 9, 2023

Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. Building a model requires specialized, hard-to-find skills — and each new task requires repeating the process. ” These large models have lowered the cost and labor involved in automation.

Enterprise 135

Enterprise Technology Modeling Cost-Benefit 135