Smart Data Collective

APRIL 29, 2020

Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data management approaches are varied and may be categorised in the following: Cloud data management. Master data management. Data transformation.

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Dataversity

AUGUST 5, 2021

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

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Dataconomy

SEPTEMBER 27, 2024

For example, Google’s BigQuery cloud data warehouse, which many companies use, is already introducing new tools that make life easier for analysts, such as searching for insights based on a specific table and monitoring data quality. What used to take days or weeks can now be done in a few hours.

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Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming.

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Alation

AUGUST 30, 2022

These range from data sources , including SaaS applications like Salesforce; ELT like Fivetran; cloud data warehouses like Snowflake; and data science and BI tools like Tableau. This expansive map of tools constitutes today’s modern data stack. In 2022.3, In 2022.3,

Data Governance 52

Data Governance Data Quality Tableau Data Analyst 52

Snorkel AI

JANUARY 11, 2023

To improve the training data quality (and reduce the number of revision cycles required to translate domain knowledge to a third-party service), the team realized they needed an alternative to hand-labeling data.

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Data Warehouse Natural Language Processing Data Scientist Cloud Data 52

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data.

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Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. Purchase date represents one customer touch point.

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Precisely

MAY 13, 2024

The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

Data Governance 52

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The MLOps Blog

MAY 17, 2023

Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines. This provides data scientists with a unified view of the data and helps them decide how the model should be trained, values for hyperparameters, etc.

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phData

FEBRUARY 5, 2024

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture. Moving historical data from a legacy system to Snowflake poses several challenges.

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Pickl AI

OCTOBER 15, 2024

ETL (Extract, Transform, Load) is a core process in data integration that involves extracting data from various sources, transforming it into a usable format, and loading it into a target system, such as a data warehouse. It supports both batch and real-time data processing , making it highly versatile.

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phData

JANUARY 24, 2024

Fivetran includes features like data movement, transformations, robust security, and compatibility with third-party tools like DBT, Airflow, Atlan, and more. Its seamless integration with popular cloud data warehouses like Snowflake can provide the scalability needed as your business grows.

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Data Warehouse Data Pipeline Data Governance Cloud Data 52

phData

JULY 19, 2023

At its core, Fivetran is a data integration platform that enables you to effortlessly connect and centralize your data from various sources into your preferred data destination, such as a data warehouse or cloud storage. Fivetran’s benefits extend to businesses across industries and sizes.

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phData

JULY 19, 2023

At its core, Fivetran is a data integration platform that enables you to effortlessly connect and centralize your data from various sources into your preferred data destination, such as a data warehouse or cloud storage. Fivetran’s benefits extend to businesses across industries and sizes.

Data Warehouse 52

Data Warehouse Database Data Pipeline SQL 52

Alation

DECEMBER 15, 2022

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

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phData

OCTOBER 12, 2022

But maybe your business users want to be able to know if the data they’re consuming is fresh and up to their standards for data quality. dbt Cloud also gives your end users certainty that the data they’re using to make decisions is clean and current. Our team of data experts are happy to assist.

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phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

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Dataversity

MARCH 22, 2021

This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]. The post Where Is the Data Technology Industry Headed? Click here to learn more about Heine Krog Iversen.

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Alation

AUGUST 11, 2021

Anthony and his governance team use data to uncover customer insights, and to discover areas where they can improve safety. Like many organizations, TMIC had a complex set of data sources and internal data warehouses. Data quality and stewardship for effective cloud governance.

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Data Governance Data Warehouse Data Classification Cloud Data 52

phData

MAY 6, 2024

Data Quality Next, dive into the details of your data. Another benefit of deterministic matching is that the process to build these identities is relatively simple, and tools your teams might already use, like SQL and dbt , can efficiently manage this process within your cloud data warehouse.

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phData

MAY 11, 2023

Snowflake has so many features that make it the leader in the Cloud Data Warehouse market. Cloning in Snowflake simply means that the data in the clone is not a copy of the original data but simply points back to the original data. Two of these tools are Terraform and phData’s own Provision tool.

Database 52

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Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. Data Validation With stored procedures, you can validate data fields, data types, and constraints on data input to maintain data quality.

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Alation

JANUARY 25, 2022

On the policy front, a feature like Policy Center empowers users to enforce and track policies at scale; this ensures that people use data compliantly, and organizations are prepared for compliance audits. How can data users navigate and understand such a complex landscape predictably? Alation Data Catalog for the data fabric.

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phData

SEPTEMBER 27, 2024

Data Quality Management : Persistent staging provides a clear demarcation between raw and processed customer data. This makes it easier to implement and manage data quality processes, ensuring your marketing efforts are based on clean, reliable data. Here’s where it gets really interesting.

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phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

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AWS Machine Learning Blog

APRIL 3, 2025

When needed, the system can access an ODAP data warehouse to retrieve additional information. The company aims to integrate additional data sources, including other mission-critical systems, into ODAP. OMRON is also exploring more advanced generative AI use cases, such as INSERT_INITIATIVES.

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Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. 5 Benefits of Data Modernization. Advanced Tooling.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

phData

OCTOBER 17, 2023

This cuts into time that can be spent delivering new data/features – and often results in leadership wondering why it is taking so long for new products to arrive (which leads to projects being cut). Additionally, frequent trust issues arise as these pipelines break or data quality suffers.

ETL 52

ETL Data Pipeline Data Engineer Data Engineering 52

Alation

AUGUST 17, 2021

Many are turning to Snowflake for its modern cloud data warehouse, which offers flexibility, cost savings, and governance capabilities across an entire data ecosystem. Alation simplifies data governance by embedding it into the UX. Are you keen to promote data literacy and data culture?

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Alation

AUGUST 26, 2021

Data intelligence has thus evolved to answer these questions, and today supports a range of use cases. Examples of Data Intelligence use cases include: Data governance. Cloud Transformation. Cloud Data Migration. Let’s take a closer look at the role of DI in the use case of data governance.

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