AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

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AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities. In such scenarios, you can use FedML Octopus.

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Precisely

FEBRUARY 12, 2024

For instance, telcos are early adopters of location intelligence – spatial analytics has been helping telecommunications firms by adding rich location-based context to their existing data sets for years. Despite that fact, valuable data often remains locked up in various silos across the organization.

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Alation

MARCH 21, 2023

For example, airlines have historically applied analytics to revenue management, while successful hospitality leaders make data-driven decisions around property allocation and workforce management. What is big data in the travel and tourism industry? Why is data analytics important for travel organizations?

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Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Businesses harness these innovations for real-time analytics, operational efficiency, and data democratisation, ensuring competitiveness in 2025. billion by 2030, with an impressive CAGR of 27.3%

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AWS Machine Learning Blog

DECEMBER 3, 2024

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. He brings extensive AI/ML and Enterprise search experience to the team with over 7 years of product leadership at AWS.

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The MLOps Blog

MAY 17, 2023

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

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Alation

MAY 2, 2023

Hospitality organizations use data analytics to unlock insights, improve operations, and maximize profits. Leveraging analytics enables companies in this space to achieve financial and operational efficiencies while delivering personalized services and offerings. What is data analytics in the hospitality industry?

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Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Modern businesses are increasingly leveraging analytics for a range of use cases. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. What is Data Analytics?

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Pickl AI

APRIL 24, 2023

The primary focus of every organisation across the industry spectrums is to harness the power of data. Here comes the role of a cloud-based data analytics platform. These cloud-based platforms empower businesses to work on bulk data and process it efficiently. However, not all analytics platforms are the same.

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Women in Big Data

MARCH 5, 2025

I had the pleasure of interviewing Anu Jekal , the CEO of Data Surge , a leading company in data and AI/ML. At Women in Big Data (WiBD), Anu has been a mentor and volunteer for almost 2 years. When I discovered the field of data analytics, it felt like a perfect fit.

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IBM Journey to AI blog

JANUARY 30, 2024

Multicloud architecture not only empowers businesses to choose a mix of the best cloud products and services to match their business needs, but it also accelerates innovation by supporting game-changing technologies like generative AI and machine learning (ML).

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Alation

MAY 2, 2023

Hospitality organizations use data analytics to unlock insights, improve operations, and maximize profits. Leveraging analytics enables companies in this space to achieve financial and operational efficiencies while delivering personalized services and offerings. What is data analytics in the hospitality industry?

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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

OCTOBER 5, 2021

Why is your data governance strategy failing? According to the Gartner report, The State of Data and Analytics Governance Is Worse Than You Think , approximately 80% of businesses readily acknowledge that high-quality data governance is essential to achieving long-term business goals, objectives, and outcomes.

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AWS Machine Learning Blog

DECEMBER 29, 2022

You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale. This is a new capability that makes it super easy to run analytics in the cloud with high performance at any scale.

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phData

APRIL 18, 2023

This is due to a fragmented ecosystem of data silos, a lack of real-time fraud detection capabilities, and manual or delayed customer analytics, which results in many false positives. Snowflake Marketplace offers data from leading industry providers such as Axiom, S&P Global, and FactSet.

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Precisely

AUGUST 12, 2024

Modern CXPs support seamless omnichannel communications, advanced capabilities like AI and ML, and ensure regulatory compliance. Data silos Limited integration capabilities Fragmented communications Workflow problems Limited scalability The fact is, your legacy systems can create great risks for your business.

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IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Precisely

FEBRUARY 9, 2024

When it comes to AI outputs, results will only be as strong as the data that’s feeding them. Trusting your data is the cornerstone of successful AI and ML (machine learning) initiatives, and data integrity is the key that unlocks the fullest potential. That approach assumes that good data quality will be self-sustaining.

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Precisely

JUNE 2, 2023

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. At the same time, there is a stronger push for real-time analytics and real-time customer access to data.

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DataRobot Blog

AUGUST 16, 2022

The survey asked companies how they used two overlapping types of tools to deploy analytical models: Data operations (DataOps) tools, which focus on creating a manageable, maintainable, automated flow of quality-assured data. ML Software Development. Survey Questions. Realistic Expectations.

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Alation

FEBRUARY 1, 2022

Sheer volume of data makes automation with Artificial Intelligence & Machine Learning (AI & ML) an imperative. Menninger outlines how modern data governance practices may deploy a basic repository of data; this can help with some level of automation. Data lakes are repositories where much of this data winds up.

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phData

APRIL 2, 2024

By leveraging cloud-based data platforms such as Snowflake Data Cloud , these commercial banks can aggregate and curate their data to understand individual customer preferences and offer relevant and personalized products. Why Use Snowflake for Commercial Banks?

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Precisely

JUNE 12, 2023

Insurance companies that use artificial intelligence and machine learning (AI/ML) technology, for example, are competing aggressively and winning market share. Lack of agility : To take advantage of the newest advances in technology, insurers must have the capacity to use their data efficiently and effectively.

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Precisely

JULY 18, 2024

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

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phData

FEBRUARY 14, 2023

Insurance companies often face challenges with data silos and inconsistencies among their legacy systems. To address these issues, they need a centralized and integrated data platform that serves as a single source of truth, preferably with strong data governance capabilities.

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phData

MAY 13, 2024

There are many challenges to overcome when doing this, and understanding them and choosing the right solutions is critical to the ultimate success and enablement of better decision-making using your ERP data. Breaking free from the constraints of legacy SAP systems creates a strategic advantage for your organization.

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IBM Journey to AI blog

JULY 3, 2024

This allows for easier integration with your existing technology investments while eliminating data silos and accelerating data-driven transformation. The following four components help build an open and trusted data foundation.

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Precisely

MAY 16, 2024

Ensure your data is accurate, consistent, and contextualized to enable trustworthy AI systems that avoid biases, improve accuracy and reliability, and boost contextual relevance and nuance. Adopt strategic practices in data integration, quality management, governance, spatial analytics, and data enrichment.

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IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

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IBM Journey to AI blog

MAY 15, 2024

According to International Data Corporation (IDC), stored data is set to increase by 250% by 2025 , with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

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Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. Only then can you extract insights across fragmented data architecture.

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Precisely

JANUARY 23, 2024

In today’s digital economy, data-driven decisions are rapidly becoming the norm. According to a 2023 survey by Drexel University’s LeBow College of Business , 77% of data and analytics professionals say that data-driven decision-making is a leading goal for their data programs.

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ODSC - Open Data Science

JUNE 7, 2023

This means that customers can easily create secure and scalable Hadoop-based data lakes that can quickly process large amounts of data with simplicity and data security in mind. Snowflake Snowflake is a cross-cloud platform that looks to break down data silos. Delta & Databricks Make This A Reality!

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Precisely

OCTOBER 12, 2023

The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, surveyed more than 450 data and analytics professionals on the state of their data programs. Intelligence. How can I be alerted about changes, anomalies, and outliers?

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phData

AUGUST 11, 2023

Data engineering in healthcare is taking a giant leap forward with rapid industrial development. Artificial Intelligence (AI) and Machine Learning (ML) are buzzwords these days with developments of Chat-GPT, Bard, and Bing AI, among others. However, data collection and analysis have been commonplace in the healthcare sector for ages.

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