The Data Governance Institute

AUGUST 6, 2020

Examples of data-related change management are: Changes to allowable values for reference tables Changes to physical data stores that impact the ability to access or protect in-scope data Changes to data models Changes to data definitions Changes to data structures Changes to data movement Changes to the structure of metadata repositories Changes to (..)

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Dataconomy

OCTOBER 17, 2023

Whether you are starting or revamping an existing data warehouse, designing a step-by-step guide can help cement your architecture design while avoiding common missteps. But It’s always better to call data warehouse experts before making a big decision.

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Smart Data Collective

NOVEMBER 24, 2021

Based on this assumption, specialists relied on false predictive data models that could only reflect a simplified picture of the possible future. In this paradigm, any minor deviations in data (which, in fact, could predict something) could simply be ignored or perceived as exceptions. Hypothesis definition.

Analytics 128

Analytics Analytics Business Intelligence Business Intelligence 128

Data Science Blog

NOVEMBER 15, 2023

New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

AWS Machine Learning Blog

FEBRUARY 27, 2024

The SageMaker project template includes seed code corresponding to each step of the build and deploy pipelines (we discuss these steps in more detail later in this post) as well as the pipeline definition—the recipe for how the steps should be run.

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Machine Learning Machine Learning ML ML 112

Mlearning.ai

FEBRUARY 13, 2023

where each word represents a key and each definition represents a value. These databases are designed for fast data retrieval and are ideal for applications that require quick data access and low latency, such as caching, session management, and real-time analytics. Cassandra and HBase are widely used with IoT 6.

Database 52

Database Data Modeling Data Models SQL 52

phData

AUGUST 18, 2023

Classify column is categorizing or organizing existing data into different buckets or definitions. Classify and Fill can be very similar if you are asking AI to categorize or organize your data. Whereas Fill will use populate types based on its own definitions. What is the Classify Column Option?

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ODSC - Open Data Science

SEPTEMBER 27, 2023

Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format. Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition.

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phData

JUNE 27, 2023

Data Lineage See exactly how your data is connected, edit on the fly, and follow your outputs as they flow downstream to your final dashboard and elements. Is dbt an Ideal Fit for YOUR Organization’s Data Stack? dbt’s addition of data freshness, quality, and cataloging is just another example of Sigma’s vision.

SQL 52

SQL Database Data Quality Data Warehouse 52

Smart Data Collective

NOVEMBER 18, 2020

This new approach has proven to be much more effective, so it is a skill set that people must master to become data scientists. Definition: Data Mining vs Data Science. Data mining is an automated data search based on the analysis of huge amounts of information. Data Mining Techniques and Data Visualization.

Data Mining 143

Data Mining Data Mining Data Mining Data Science 143

Heartbeat

DECEMBER 7, 2023

Data should be designed to be easily accessed, discovered, and consumed by other teams or users without requiring significant support or intervention from the team that created it. Data should be created using standardized data models, definitions, and quality requirements.

Data Governance 52

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AWS Machine Learning Blog

NOVEMBER 15, 2023

A full example of the models dictionary is available in the GitHub repository. For example, if your preprocessors dictionary contains 10 recipes and you have 5 model definitions in the models dictionary, the newly created pipelines dictionary contains 50 preprocessor-model pipelines that are evaluated during HPO.

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Algorithm AWS ML ML 86

Smart Data Collective

APRIL 14, 2021

Main features include the ability to access and operationalize data through the LookML library. It also allows you to create your data and creating consistent dataset definitions using LookML. Formerly known as Periscope, Sisense is a business intelligence tool ideal for cloud data teams.

Business Intelligence 134

Business Intelligence Business Intelligence Tableau SQL 134

Alation

FEBRUARY 13, 2020

This achievement is a testament not only to our legacy of helping to create the data catalog category but also to our continued innovation in improving the effectiveness of self-service analytics. A broader definition of Business Intelligence. Enabling workers to find the right data is crucial to promoting self-service analytics.

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Tableau

OCTOBER 8, 2021

With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

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Tableau

OCTOBER 8, 2021

With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

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Tableau Analytics Analytics Machine Learning 98

Pickl AI

AUGUST 29, 2023

These statistical models help in providing insights and understand complex phenomena along with aiding in decision-making process. The process of statistical modelling involves the following steps: Problem Definition: Here, you clearly define the research question first that you want to address using statistical modeling.

Data Scientist 52

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AWS Machine Learning Blog

JUNE 5, 2023

Hyperparameter overview When training any machine learning (ML) model, you are generally dealing with three types of data: input data (also called the training data), model parameters, and hyperparameters. You use the input data to train your model, which in effect learns your model parameters.

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Dataconomy

MARCH 6, 2023

This includes its business processes, technology infrastructure, and data architecture. Definition of enterprise architecture Enterprise architecture is the process of creating and managing a holistic view of an organization’s current and future state. It includes data models, data flows, and data governance policies.

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Hacker News

FEBRUARY 11, 2024

The quality of the roles was about the same as I normally get (albeit at a much higher rate) – some I really liked, some were OK, and some were definitely not for me. Maybe I could see more profile viewers, I am not sure, but it is definitely not showing who all of them are. Applying to known companies.

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Python Database Data Modeling Data Models 181

Pickl AI

DECEMBER 4, 2023

and ‘‘What is the difference between Data Intelligence and Artificial Intelligence ?’. Criteria Data Intelligence Data Information Artificial Intelligence Data Analysis Definition Data Intelligence involves the analysis and interpretation of data to derive actionable insights. Look at the table below.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

Heartbeat

MARCH 21, 2023

In the context of time series, model monitoring is particularly important as time series data can be highly dynamic because change is definite over time in ways that can impact the accuracy of the model.

Exploratory Data Analysis 59

Exploratory Data Analysis EDA Machine Learning Machine Learning 59

AWS Machine Learning Blog

JUNE 22, 2023

The ML model takes in the historical sequence of machine events and other metadata and predicts whether a machine will encounter a failure in a 6-hour future time window. He works on pioneering solutions for various industries using statistical modeling and machine learning techniques.

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AWS ML ML Machine Learning 82

Alation

APRIL 26, 2021

In your organization, are you ever confused by different definitions of business terms? If you’re thinking “business term definitions” are straightforward, think again. A business glossary helps an organization agree and align on internal definitions. List of business terms and their definitions.

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Database Machine Learning Machine Learning Database Administration 52

ML Review

FEBRUARY 26, 2018

Since intentions determine the subsequent domain identification flow, the intention stratum is a necessary first step in initiating contextual and domain data model processes. Efforts in gathering data and refining knowledge graphs will contribute to IHCI’s development.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Alation

MAY 31, 2023

They collaborate with IT professionals, business stakeholders, and data analysts to design effective data infrastructure aligned with the organization’s goals. Their broad range of responsibilities include: Design and implement data architecture. Maintain data models and documentation.

Data Governance 52

Data Governance Data Quality Data Silos Data Modeling 52

phData

MAY 25, 2023

While the loss of certain DAX functions is definitely a shortcoming that we hope Microsoft will address in the near future, the impact of these lost DAX functions is not necessarily as big as you would expect. Creating an efficient data model can be the difference between having good or bad performance, especially when using DirectQuery.

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Power BI Analytics Analytics Azure 84

DrivenData Labs

MARCH 30, 2023

The financial crime detection track definitely fell in that category! Summary of approach : In our solution, the financial transaction messaging system and its network of banks jointly extract feature values to improve the utility of a machine learning model for anomalous payment detection.

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

phData

APRIL 10, 2023

A truly governed self-service analytics model puts data modeling responsibilities in the hands of IT and report generation and analysis in the hands of business users who will actually be doing the analysis. Business users build reports on an IT-owned and IT-created data model that is focused on reporting solutions.

Analytics 52

Analytics Analytics Data Governance Data Modeling 52

Alation

NOVEMBER 4, 2021

However, I paused and asked myself: What is the value that customers of Alation actually got for non-compliance or data security use cases? The value of the data catalog depends on the audience. For data modelers, value arose from spending less time finding data and more time modeling data.

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IBM Journey to AI blog

OCTOBER 30, 2023

A successful public health response to a future pandemic will rely on collecting and managing critical data, investing in smart, capable and flexible data modernization systems, and preparing people with the proper knowledge and skills. Lesson 1: Use a data model built for public health.

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Data Modeling Data Models Data Silos Machine Learning 67

Hacker News

JULY 18, 2023

What if you could automatically shard your PostgreSQL database across any number of servers and get industry-leading performance at scale without any special data modelling steps? Schema-based sharding has almost no data modelling restrictions or special steps compared to unsharded PostgreSQL.

Database 123

Database SQL Data Modeling Data Models 123

Iguazio

JANUARY 22, 2024

Definitions: Foundation Models, Gen AI, and LLMs Before diving into the practice of productizing LLMs, let’s review the basic definitions of GenAI elements: Foundation Models (FMs) - Large deep learning models that are pre-trained with attention mechanisms on massive datasets.

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phData

SEPTEMBER 13, 2023

Some third-party tools like Fivetran provide exceptional data modeling capabilities, which can be extremely helpful down the road. This is the easiest and fastest way to onboard your data into Snowflake. It also automates the creation of Data Definition Language (DDL) on the Snowflake side, saving setup time.

Tableau 52

Tableau Data Pipeline Data Silos Analytics 52

Tableau

APRIL 18, 2022

Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Data preparation.

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Tableau

APRIL 18, 2022

Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Data preparation.

Tableau 97

Tableau Data Quality Analytics Analytics 97

Tableau

SEPTEMBER 23, 2021

No single source of truth: There may be multiple versions or variations of similar data sets, but which is the trustworthy data set users should default to? Missing data definitions and formulas: People need to understand exactly what the data represents, in the context of the business, to use it effectively.

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Data Governance Analytics Analytics Tableau 91