Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Data Mesh on Azure Cloud with Databricks and Delta Lake for Applications of Business Intelligence, Data Science and Process Mining.

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IBM Journey to AI blog

SEPTEMBER 5, 2024

The best way to build a strong foundation for data success is through effective data governance. Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success.

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The Data Administration Newsletter

FEBRUARY 28, 2023

The project management profession, like many others, faces an emergent threat from artificial intelligence (AI)-based technologies. Gartner has predicted that by 2030, upwards to 80% of project management work will be automated by artificial intelligence (AI). Although 80% is arguably a bit extreme, I expect […]

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Dataconomy

APRIL 16, 2025

This modular approach allows businesses to assemble tools and techniques that perfectly fit their specific needs, rather than relying on less flexible monolithic systems. Composable analytics refers to an agile, adaptable framework for data analytics that allows users to create customized analytical environments using modular components.

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Data Science Blog

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. For analysis the way of Business Intelligence this normalized data model can already be used.

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Precisely

NOVEMBER 5, 2024

While data quality issues are nothing new, the impact of these problems is more impactful on business outcomes than ever before. That’s due to the speed at which advanced analytics, business intelligence (BI), and artificial intelligence (AI) are progressing.

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Dataconomy

MARCH 28, 2025

It merges the principles of decision theory, data science, and artificial intelligence into a cohesive framework, enriching the decision-making landscape. Definition and scope Understanding decision intelligence requires recognizing its multi-faceted nature.

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Alation

JULY 19, 2021

This requires a metadata management solution to enable data search & discovery and data governance, both of which empower access to both the metadata and the underlying data to those who need it. In today’s world, metadata management best practices call for a data catalog. Administrative information.

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Defined.ai blog

AUGUST 10, 2023

Welcome to the world of financial data, where every digit has a story to tell, and Artificial Intelligence (AI) assumes the role of a compelling storyteller. With more companies shifting towards data-driven decision-making, understanding financial data and leveraging AI’s power has never been more crucial.

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Pickl AI

NOVEMBER 5, 2024

Introduction Business Intelligence (BI) tools are crucial in today’s data-driven decision-making landscape. They empower organisations to unlock valuable insights from complex data. Tableau and Power BI are leading BI tools that help businesses visualise and interpret data effectively. billion in 2023.

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Precisely

APRIL 25, 2024

Jean-Paul sat down for an interview where we discussed his background as a former CDO, the challenges he faced, and how he developed his unique perspective and data governance expertise. After starting my career in banking IT, I turned to consulting, and more specifically to Business Intelligence (BI) in 2004.

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Dataconomy

MAY 17, 2023

Welcome to the exciting world of artificial intelligence in sales! In today’s rapidly evolving business landscape, organizations are increasingly turning to cutting-edge technologies to enhance their sales strategies and gain a competitive edge. How is artificial intelligence used in sales?

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Dataversity

JULY 21, 2022

Despite its many benefits, the emergence of high-performance machine learning systems for augmented analytics over the last 10 years has led to a growing “plug-and-play” analytical culture, where high volumes of opaque data are thrown arbitrarily at an algorithm until it yields useful business intelligence.

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IBM Journey to AI blog

JUNE 29, 2023

This may involve consolidating data from enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, supply chain management systems, and other relevant sources. Implementing advanced analytics and business intelligence tools can further enhance data analysis and decision-making capabilities.

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IBM Journey to AI blog

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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IBM Journey to AI blog

MAY 17, 2024

The push to enhance productivity, use resources wisely, and boost sustainability through data-driven decision-making is stronger than ever. Yet, the low adoption rates of business intelligence (BI) tools present a significant hurdle.

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Pickl AI

APRIL 27, 2023

Moreover, Business Intelligence and analytics are already being actively used by organizations to improvise their operations. AI will Be Transforming The Way Business Operates Artificial Intelligence has already made strides across the business domain. All this falls under the umbrella of Data Governance.

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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

OCTOBER 2, 2024

This includes implementing access controls, data governance policies, and proactive monitoring and alerting to make sure sensitive information is properly secured and monitored. For cases where you need a semantic understanding of your data, you can use Amazon Kendra for intelligent enterprise search.

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Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

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Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? 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.

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IBM Journey to AI blog

MAY 9, 2023

. “The media and entertainment industry has undergone a significant digital transformation, with viewers consuming content across different devices and platforms,” said Vitaly Tsivin, EVP Business Intelligence at AMC Networks. ” Notably, watsonx.data runs both on-premises and across multicloud environments.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

Storage Optimization: Data warehouses use columnar storage formats and indexing to enhance query performance and data compression. Without proper version control, different users may inadvertently overwrite or modify data, leading to potential data integrity issues and confusion.

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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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IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. Chat with a data management expert The post Why optimize your warehouse with a data lakehouse strategy appeared first on IBM Blog.

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Alation

AUGUST 5, 2021

Organizations must be able to locate the totality of an individual’s information almost instantly and without missing even a fraction of the collected data because of inaccurate or inconsistent data. The abundance of data systems has also made the monitoring of complicated tasks even more challenging.

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Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Exploring technologies like Data visualization tools and predictive modeling becomes our compass in this intricate landscape.

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The Data Administration Newsletter

APRIL 17, 2024

The focus of my last column, titled Crossing the Data Divide: Data Catalogs and the Generative AI Wave, was on the impact of large language models (LLM) and generative artificial intelligence (AI) and how we disseminate knowledge throughout the enterprise and the future role of the data catalogs.

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Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

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IBM Journey to AI blog

JULY 13, 2023

This is the practice of creating, updating and consistently enforcing the processes, rules and standards that prevent errors, data loss, data corruption, mishandling of sensitive or regulated data, and data breaches.

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Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management. What is Big Data?

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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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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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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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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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Pickl AI

SEPTEMBER 11, 2024

Data as a Service (DaaS) DaaS allows organisations to access and integrate data from various sources without the need for complex data management. It provides APIs and data connectors to facilitate data ingestion, transformation, and delivery.

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Pickl AI

SEPTEMBER 5, 2024

Operations Analysts are increasingly leveraging advanced analytics tools to gain deeper insights into business processes. Technologies such as machine learning and artificial intelligence are being integrated into Data Analysis, allowing analysts to predict trends and identify potential issues before they arise.

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