ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. This includes its structure, content, and relationships between variables.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Smart Data Collective

OCTOBER 1, 2019

Other uses extend to student support, which for example, makes recommendations on courses and career paths based on how students with similar data profiles performed in the past. AI systems allow for the analysis of more granular patterns of the student’s data profile. Perils of Depending on AI in Higher Education.

Artificial Intelligence 109

Artificial Intelligence Artificial Intelligence Big Data Big Data 109

Alation

JANUARY 20, 2022

To be clear, data quality is one of several types of data governance as defined by Gartner and the Data Governance Institute. Quality policies for data and analytics set expectations about the “fitness for purpose” of artifacts across various dimensions. Step 4: Data Sources. Step 5: Data Profiling.

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Data Quality Data Governance Data Profiling Clean Data 94

IBM Journey to AI blog

JULY 13, 2023

Data quality uses those criteria to measure the level of data integrity and, in turn, its reliability and applicability for its intended use. Data integrity To achieve a high level of data integrity, an organization implements processes, rules and standards that govern how data is collected, stored, accessed, edited and used.

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Data Quality Data Profiling Data Governance Machine Learning 74

Precisely

SEPTEMBER 9, 2024

Key Takeaways: • Implement effective data quality management (DQM) to support the data accuracy, trustworthiness, and reliability you need for stronger analytics and decision-making. Embrace automation to streamline data quality processes like profiling and standardization. It reveals several critical insights: 1.

Data Quality 64

Data Quality Data Profiling Data Lakes Analytics 64

Dataversity

DECEMBER 7, 2020

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

Data Warehouse 90

Data Warehouse Business Intelligence Business Intelligence Analytics 90

Smart Data Collective

SEPTEMBER 21, 2021

Data fabric is an architecture and set of data services that provide capabilities to seamlessly integrate and access data from multiple data sources like on-premise and cloud-native platforms. The data can also be processed, managed and stored within the data fabric.

Data Quality 131

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Precisely

FEBRUARY 20, 2025

If you cant use predictive analytics and make quick, confident data-driven decisions, you risk falling behind to your competitors that can. Solution: Ensure real-time insights and predictive analytics are both accurate and actionable with data integration.

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Data Silos AI AI Data Quality 69

DataRobot Blog

OCTOBER 9, 2017

Excel has long been the tool for business analysts to perform lightweight data preparation tasks – identifying outliers and errors, aggregating values, and combining data into one spreadsheet for analytics. However, all too often, business users waste time using Excel to manually profile and process data.

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Data Preparation Data Profiling Data Governance Machine Learning 52

Alation

SEPTEMBER 7, 2021

In addition, Alation provides a quick preview and sample of the data to help data scientists and analysts with greater data quality insights. Alation’s deep data profiling helps data scientists and analysts get important data profiling insights. Operationalize data governance at scale.

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Precisely

JUNE 26, 2023

Forward-thinking businesses invest in digital transformation, cloud adoption, advanced analytics and predictive modeling, and supply chain resiliency. 2023 Data Integrity Trends & Insights Results from a Survey of Data and Analytics Professionals Read the report Here are some of the top takeaways that stood out to panelists.

Data Quality 52

Data Quality Data Silos Analytics Data Governance 52

Pickl AI

OCTOBER 18, 2023

– Predictive analytics to assess data quality issues before they become critical. Data Cleansing and Standardization – Automated data cleansing using AI algorithms to correct errors, remove duplicates, and standardize formats. – Natural Language Processing (NLP) for text data standardization. .

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The MLOps Blog

JUNE 27, 2023

Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. You can define expectations about data quality, track data drift, and monitor changes in data distributions over time. Share features across the organization.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

OCTOBER 10, 2023

Significance of Data For delving deeper into the concepts of Data Observability and Data Quality, it’s important to understand the relevance of data in the modern business realm. Data empowers organizations to understand customer behavior, streamline operations, and make data-driven decisions.

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Data Observability Data Quality Data Governance Data Pipeline 52

IBM Journey to AI blog

JANUARY 5, 2023

Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable. Perform data profiling (the process of examining, analyzing and creating summaries of datasets). Creating a data architecture roadmap.

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Data Quality Data Lakes Data Warehouse Big Data 52

Alation

MAY 24, 2022

Alation has been leading the evolution of the data catalog to a platform for data intelligence. Higher data intelligence drives higher confidence in everything related to analytics and AI/ML. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

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Data Quality Data Governance ETL Data Observability 98

Dataconomy

JULY 28, 2023

Microsoft Power BI has been recently added to Microsoft’s most advanced data solution, Microsoft Fabric ( Image Credit ) Tableau Tableau is a powerful data preparation tool that serves as a solid foundation for data analytics.

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Precisely

SEPTEMBER 11, 2023

By 2025, 80% of mainstream data quality vendors will expand their product capabilities to provide greater data insights by discovering patterns, trends, data relationships, and error resolution.

Data Quality 52

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Alation

JANUARY 13, 2022

The definition we are going with here is Gartner’s and, to them, there is no single vendor that addresses the complete set of needs required to build a data fabric (at least not today). Gartner defines data fabric as a “design concept that serves as an integrated layer (fabric) of data and connecting processes.”.

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

AWS Machine Learning Blog

APRIL 18, 2023

The sample set of de-identified, already publicly shared data included thousands of anonymized user profiles, with more than fifty user-metadata points, but many had inconsistent or missing meta-data/profile information. Vamshi Krishna Enabothala is a Sr. Applied AI Specialist Architect at AWS.

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Pickl AI

OCTOBER 19, 2023

Define data ownership, access rights, and responsibilities within your organization. A well-structured framework ensures accountability and promotes data quality. Data Quality Tools Invest in quality data management tools. Here’s how: Data Profiling Start by analyzing your data to understand its quality.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

Pickl AI

OCTOBER 11, 2023

Key Features Benefit from the real-time surveillance thus, it helps in identifying potential issues in real-time It comes with advanced analytical capacities contributing to well-informed decision-making; Intuitively explore and grasp the intricacies of data.

Data Observability 52

Data Observability Data Quality Data Pipeline Data Governance 52

Alation

DECEMBER 21, 2022

Early on, analysts used data catalogs to find and understand data more quickly. Increasingly, data catalogs now address a broad range of data intelligence solutions, including self-service analytics , data governance , privacy , and cloud transformation.

Data Quality 52

Data Quality Data Warehouse Data Profiling Data Governance 52

Dataconomy

FEBRUARY 23, 2023

Cloud computing: Cloud computing provides a scalable and cost-effective solution for managing and processing large volumes of data. Cloud providers offer various services such as storage, compute, and analytics, which can be used to build and operate big data systems.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

Dataversity

FEBRUARY 1, 2021

In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […].

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Dataversity

JANUARY 11, 2021

In Part 1 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […].

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

The MLOps Blog

MAY 17, 2023

A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse. Further processes or workflows can then easily utilize this data to create business intelligence and analytics solutions. This involves looking at the data structure, relationships, and content.

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The MLOps Blog

MARCH 15, 2023

Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Data Consumption : You have reached a point where the data is ready for consumption for AI, BI & other analytics.

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phData

SEPTEMBER 1, 2023

Thankfully, Sigma Computing and Snowflake Data Cloud provide powerful tools for HCLS companies to address these data analytics challenges head-on. In this blog, we’ll explore 10 pressing data analytics challenges and discuss how Sigma and Snowflake can help.

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Alation

AUGUST 26, 2021

Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more. Data Intelligence: Origin, Evolution, Use Cases. Examples of Data Intelligence use cases include: Data governance.

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Alation

JULY 6, 2021

Finally, they need control and authority to make decisions that improve data governance. But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. Top Challenges. Lack of Control.

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Data Governance Data Quality Data Silos Data Profiling 52

Mlearning.ai

JUNE 25, 2023

Using this APP provision, user’s can simply ask question related to their input data and get the corresponding data analysis results as response.

Data Analysis 52

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Dataconomy

MARCH 26, 2025

Data integration: Merges information from CRM platforms and marketing automation systems for a comprehensive view of customer interactions. Creation of reliable datasets: Prepares datasets for analytics use cases, ensuring reliability for thorough analysis.

ETL 91

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