Data Science Dojo

JULY 6, 2023

These tools provide data engineers with the necessary capabilities to efficiently extract, transform, and load (ETL) data, build data pipelines, and prepare data for analysis and consumption by other applications. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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IBM Journey to AI blog

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

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Tableau

OCTOBER 7, 2024

This technology sprawl often creates data silos and presents challenges to ensuring that organizations can effectively enforce data governance while still providing trusted, real-time insights to the business.

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Dataconomy

SEPTEMBER 4, 2023

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

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The Data Administration Newsletter

DECEMBER 20, 2022

Over the past few months, my team in Castlebridge and I have been working with clients delivering training to business and IT teams on data management skills like data governance, data quality management, data modelling, and metadata management.

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phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

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Dataversity

FEBRUARY 4, 2022

But decisions made without proper data foundations, such as well-constructed and updated data models, can lead to potentially disastrous results. For example, the Imperial College London epidemiology data model was used by the U.K. Government in 2020 […].

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ODSC - Open Data Science

APRIL 28, 2023

These are critical steps in ensuring businesses can access the data they need for fast and confident decision-making. As much as data quality is critical for AI, AI is critical for ensuring data quality, and for reducing the time to prepare data with automation. How does this all tie into AI/ML?

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

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Precisely

OCTOBER 23, 2023

An ERP does not do data quality very well. CRM’s, likewise, does a poor job of undating data according to consistent standards. Very often, key business users conflate MDM with various tasks or components of data science and data management. Others regard it as a data modeling platform.

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The MLOps Blog

JUNE 27, 2023

Model versioning, lineage, and packaging : Can you version and reproduce models and experiments? Can you see the complete model lineage with data/models/experiments used downstream? It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale.

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Precisely

OCTOBER 16, 2023

Consistency, accuracy, and completeness are aspects of data integrity, of course, but true data integrity extends much further than just data quality. The broader access granted by data democratization amplifies both the importance and the challenges of maintaining data integrity.

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Alation

AUGUST 16, 2022

This week, IDC released its second IDC MarketScape for Data Catalogs report, and we’re excited to share that Alation was recognized as a leader for the second consecutive time. But do they empower many user types to quickly find trusted data for a business decision or data model? Functionality and Range of Services.

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Data Quality Data Governance Cloud Data Data Engineer 52

Precisely

MAY 1, 2023

Virtually every enterprise on the planet invests heavily in data. Integration, data quality, data governance, location intelligence, and enrichment are driving trust and delivering value. How can organizations maximize their ROI on their investments in data integrity?

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Data Governance Data Modeling Data Models Data Quality 52

Pickl AI

JUNE 23, 2023

Continuous Learning and Iteration Data-centric AI systems often incorporate mechanisms for continuous learning and adaptation. As new data becomes available, the models can be retrained or fine-tuned to improve their performance over time. Focuses on refining and updating the model architecture and parameters.

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Precisely

MARCH 27, 2023

Transforming Go-to-Market After years of acquiring and integrating smaller companies, a $37 billion multinational manufacturer of confectionery, pet food, and other food products was struggling with complex and largely disparate processes, systems, and data models that needed to be normalized. million in annual recurring savings.

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Data Quality Data Lakes Data Governance Data Modeling 52

Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Introduction In today’s data-driven landscape, organisations are increasingly reliant on Data Analytics to inform decision-making and drive business strategies.

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Data Quality Data Warehouse Data Governance Analytics 52

phData

AUGUST 10, 2023

In data vault implementations, critical components encompass the storage layer, ELT technology, integration platforms, data observability tools, Business Intelligence and Analytics tools, Data Governance , and Metadata Management solutions. This can create data quality challenges if not addressed properly.

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SQL Data Observability Data Quality Data Pipeline 52

Alation

FEBRUARY 13, 2020

IDC Innovators: Data Intelligence Software Platforms, 2019 Report. In the latest IDC Innovators: Data Intelligence Software Platforms, 2019 3 report, Alation was profiled as one vendor disrupting the data integration and integrity software market with a differentiated data intelligence software platform.

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Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Early on, analysts used data catalogs to find and understand data more quickly.

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Precisely

MARCH 7, 2024

According to a 2023 study from the LeBow College of Business , data enrichment and location intelligence figured prominently among executives’ top 5 priorities for data integrity. 53% of respondents cited missing information as a critical challenge impacting data quality. What is data integrity?

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In contrast, data warehouses and relational databases adhere to the ‘Schema-on-Write’ model, where data must be structured and conform to predefined schemas before being loaded into the database.

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phData

APRIL 10, 2023

This decision-making process is exactly what governed self-service analytics is all about. 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.

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Heartbeat

DECEMBER 7, 2023

What are the new data governance trends, “Data Fabric” and “Data Mesh”? I decided to write a series of blogs on current topics: the elements of data governance that I have been thinking about, reading, and following for a while. Advantages: Consistency ensures trust in data governance.

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Pickl AI

DECEMBER 4, 2023

Exploring technologies like Data visualization tools and predictive modeling becomes our compass in this intricate landscape. Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence.

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The Data Administration Newsletter

JANUARY 17, 2024

Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers on effectively leveraging AI within business operations.

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AI AI Data Quality Data Governance 122

Pickl AI

JUNE 11, 2024

Clearly defining your objectives will guide critical decisions regarding data selection, modelling approaches, and reporting strategies. Ensure Data Quality Data quality is the cornerstone of a successful data warehouse. Embrace a well-structured data model that aligns with your business needs.

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Dataversity

JUNE 19, 2023

In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline.

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Dataversity

MAY 1, 2023

Many organizations have mapped out the systems and applications of their data landscape. Many have modeled their data domains and key attributes. The remainder of this point of view will explain why connecting […] The post Connecting the Three Spheres of Data Management to Unlock Value appeared first on DATAVERSITY.

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Data Quality Data Governance Data Models Data Modeling 97

Pickl AI

JULY 25, 2023

Data Integration and ETL (Extract, Transform, Load) Data Engineers develop and manage data pipelines that extract data from various sources, transform it into a suitable format, and load it into the destination systems. Data Quality and Governance Ensuring data quality is a critical aspect of a Data Engineer’s role.

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Precisely

MARCH 9, 2023

Processing speeds were considerably slower than they are today, so large volumes of data called for an approach in which data was staged in advance, often running ETL (extract, transform, load) processes overnight to enable next-day visibility to key performance indicators.

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Iguazio

FEBRUARY 20, 2024

This includes management vision and strategy, resource commitment, data and tech and operating model alignment, robust risk management and change management. This helps address risks and improve data quality. You can watch the entire webinar here.

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ODSC - Open Data Science

APRIL 26, 2023

Because of this, they will be required to work closely with business stakeholders, data teams, and even other tech-focused members of an organization to sure that the needs of the organization are met and comply with overall business objectives.

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The Data Administration Newsletter

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

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Pickl AI

MAY 11, 2023

Their prime focus is to keep a tab on data collection and ensure that the exchange and movement of data are as per the policies. Data Modeling These are simple diagrams of the system and the data stored in it. It helps you to view how the data flows through the system.

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AWS Machine Learning Blog

AUGUST 21, 2023

Our customers wanted the ability to connect to Amazon EMR to run ad hoc SQL queries on Hive or Presto to query data in the internal metastore or external metastore (such as the AWS Glue Data Catalog ), and prepare data within a few clicks. Let’s look at some example transforms.

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