IBM Journey to AI blog

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

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IBM Journey to AI blog

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

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AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

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Tableau

MAY 11, 2022

Data fabrics are gaining momentum as the data management design for today’s challenging data ecosystems. At their most basic level, data fabrics leverage artificial intelligence and machine learning to unify and securely manage disparate data sources without migrating them to a centralized location.

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Tableau

MAY 11, 2022

Data fabrics are gaining momentum as the data management design for today’s challenging data ecosystems. At their most basic level, data fabrics leverage artificial intelligence and machine learning to unify and securely manage disparate data sources without migrating them to a centralized location.

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IBM Journey to AI blog

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

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AWS Machine Learning Blog

APRIL 30, 2025

ENGIEs One Data team partnered with AWS Professional Services to develop an AI-powered chatbot that enables natural language conversation search within ENGIEs Common Data Hub data lake, over 3 petabytes of data.

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Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Data Lakes allows for flexibility in handling different data types.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

The following diagram shows two different data scientist teams, from two different AWS accounts, who share and use the same central feature store to select the best features needed to build their ML models. This enhances data accessibility and utilization, allowing teams in different accounts to use shared features for their ML workflows.

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Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

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Data Pipeline Data Governance Data Lakes Data Warehouse 69

Pickl AI

SEPTEMBER 17, 2024

NoSQL Databases NoSQL databases like MongoDB or Cassandra are designed to handle unstructured or semi-structured data efficiently. Data Lakes Data lakes are centralised repositories that allow organisations to store all their structured and unstructured data at any scale.

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IBM Journey to AI blog

APRIL 25, 2023

Benefits of optimizing across your data warehouse and data lakehouse Optimizing workloads across a data warehouse and a data lakehouse by sharing data using open formats can reduce costs and complexity.

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IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

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Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

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IBM Journey to AI blog

JULY 3, 2024

Multiple data applications and formats make it harder for organizations to access, govern, manage and use all their data for AI effectively. Scaling data and AI with technology, people and processes Enabling data as a differentiator for AI requires a balance of technology, people and processes.

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Pickl AI

AUGUST 9, 2024

Data Lake vs. Data Warehouse Distinguishing between these two storage paradigms and understanding their use cases. Students should learn how data lake s can store raw data in its native format, while data warehouses are optimised for structured data.

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Pickl AI

JUNE 11, 2024

Self-Service Analytics User-friendly interfaces and self-service analytics tools empower business users to explore data independently without relying on IT departments. Ensure Data Quality Data quality is the cornerstone of a successful data warehouse.

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Pickl AI

DECEMBER 11, 2024

Implement tools that allow real-time data integration and transformation to maintain accuracy and timeliness. For example, adopting a data lake or warehouse architecture can centralise your data while eliminating duplication.

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Pickl AI

OCTOBER 10, 2024

Support for Advanced Analytics : Transformed data is ready for use in Advanced Analytics, Machine Learning, and Business Intelligence applications, driving better decision-making. Using data transformation tools is key to staying competitive in a data-driven world, offering both efficiency and reliability.

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Alation

FEBRUARY 13, 2020

In his book titled “The Fourth Industrial Revolution,” Klaus Schwab describes the age as, “characterized by a much more ubiquitous and mobile internet, by smaller and more powerful sensors that have become cheaper, and by artificial intelligence and machine learning.” Artificial intelligence without human collaboration fails.

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Alation

FEBRUARY 20, 2020

At the start of our journey, we had no idea what combination of search, descriptions, crawling, indexing, interface design, and algorithms would enable people to most easily find, understand and trust data. Today, CDOs in a wide range of industries have a mechanism for empowering their organizations to leverage data.

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ODSC - Open Data Science

JUNE 12, 2023

From a data governance perspective, this is a massive risk to organizations by exposing them to the whole laundry of privacy and security breaches. A Datamart is a self-service BI solution containing a self-service data preparation (or ETL) layer and a data model (or semantic layer).

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ODSC - Open Data Science

JANUARY 18, 2024

This means that not only do the proper infrastructures need to be created, and maintained, but data engineers will be at the forefront of data governance and access to ensure that no outside actors or black hats gain access which could spell compliance doom for any company.

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IBM Journey to AI blog

JULY 7, 2023

Yet, facilitating compliance is challenging as data sets, organizational structures and processes become increasingly complex. For example, much of today’s data resides across a hybrid multicloud environment, on-prem and in multiple clouds and data lakes.

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Pickl AI

OCTOBER 17, 2024

The primary purpose of loading is to make the data accessible to end-users and applications, enabling organisations to derive meaningful insights and support decision-making. Talend : An open-source ETL tool that provides extensive connectivity options and data transformation features, allowing customisation and scalability.

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Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Data Science Blog

MARCH 14, 2023

Von Big Data über Data Science zu AI Einer der Gründe, warum Big Data insbesondere nach der Euphorie wieder aus der Diskussion verschwand, war der Leitspruch “S**t in, s**t out” und die Kernaussage, dass Daten in großen Mengen nicht viel wert seien, wenn die Datenqualität nicht stimme.

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