IBM Journey to AI blog

MAY 9, 2023

Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

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IBM Journey to AI blog

OCTOBER 30, 2023

Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

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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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phData

SEPTEMBER 15, 2023

Salesforce Sync Out is a crucial tool that enables businesses to transfer data from their Salesforce platform to external systems like Snowflake, AWS S3, and Azure ADLS. Warehouse for loading the data (start with XSMALL or SMALL warehouses).

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IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata.

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Precisely

JULY 18, 2024

Without access to all critical and relevant data, the data that emerges from a data fabric will have gaps that delay business insights required to innovate, mitigate risk, or improve operational efficiencies. You must be able to continuously catalog, profile, and identify the most frequently used data.

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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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Dataversity

DECEMBER 14, 2020

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

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Precisely

NOVEMBER 11, 2024

This involves integrating customer data across various channels – like your CRM systems, data warehouses, and more – so that the most relevant and up-to-date information is used consistently in your customer interactions. Focus on high-quality data. Data quality is essential for personalization efforts.

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Precisely

NOVEMBER 11, 2024

This involves integrating customer data across various channels – like your CRM systems, data warehouses, and more – so that the most relevant and up-to-date information is used consistently in your customer interactions. Focus on high-quality data. Data quality is essential for personalization efforts.

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Alation

MARCH 29, 2022

The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos. During the 1990s, attempts were made to tackle challenges including: Inefficient data silos.

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Pickl AI

JUNE 28, 2023

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. It ensures that the integrated data is available for analysis and reporting.

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DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. According to Flexera 1 , 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy.

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ODSC - Open Data Science

JUNE 7, 2023

Data has to be stored somewhere. Data warehouses are repositories for your cleaned, processed data, but what about all that unstructured data your organization is starting to notice? What is a data lake? Snowflake Snowflake is a cross-cloud platform that looks to break down data silos.

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IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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phData

SEPTEMBER 20, 2023

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.

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Alation

APRIL 27, 2023

Article reposted with permission from Eckerson ABSTRACT: Data mesh is giving many of us from the data warehouse generation a serious case of agita. But, my fellow old-school data tamers, it’s going to be ok. It’s a subject that’s giving many of us from the data warehouse generation a serious case of agita.

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AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

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Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Ensure the behaves the way you want it to— especially sensitive data and access. Data integration.

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Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Ensure the behaves the way you want it to— especially sensitive data and access. Data integration.

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Precisely

JULY 12, 2024

) Obviously, data quality is a component of data integrity, but it is not the only component. Data observability: P revent business disruption and costly downstream data and analytics issues using intelligent technology that proactively alerts you to data anomalies and outliers.

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The MLOps Blog

MAY 17, 2023

These pipelines assist data scientists in saving time and effort by ensuring that the data is clean, properly formatted, and ready for use in machine learning tasks. Moreover, ETL pipelines play a crucial role in breaking down data silos and establishing a single source of truth.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Instead, a core component of decentralized clinical trials is a secure, scalable data infrastructure with strong data analytics capabilities. Amazon Redshift is a fully managed cloud data warehouse that trial scientists can use to perform analytics.

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IBM Journey to AI blog

FEBRUARY 19, 2024

Figure 2: The data product lifecycle The banking industry, for example, faces the following challenges: Competition from agile and innovative financial technology and challenger banks. Organizational data silos that impede a unified customer experience. High degree of regulatory control. Need to protect sensitive information.

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Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics.

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Alation

APRIL 27, 2023

Article reposted with permission from Eckerson ABSTRACT: Data mesh is giving many of us from the data warehouse generation a serious case of agita. But, my fellow old-school data tamers, it’s going to be ok. It’s a subject that’s giving many of us from the data warehouse generation a serious case of agita.

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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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Dataconomy

APRIL 27, 2023

On the other hand, OLAP systems use a multidimensional database, which is created from multiple relational databases and enables complex queries involving multiple data facts from current and historical data. An OLAP database may also be organized as a data warehouse.

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phData

JULY 14, 2023

You can store and access your structured, semi-structured, and unstructured data in one location and gain seamless access to external data with similar scale and speed. Snowflake’s cloud-based data warehouse can be used to store and query large amounts of data from multiple sources, such as ad networks, DSPs, and SSPs.

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phData

FEBRUARY 27, 2024

The Snowflake Data Cloud is a cloud-based data warehouse that is becoming increasingly popular among businesses of all sizes. Establish data governance guidelines. Define clear data governance guidelines to ensure data consistency, integrity, and security across multiple accounts.

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phData

AUGUST 11, 2023

Real-time data analysis could also detect irregular heartbeats that could save lives. How AI and ML Can Leverage the Data Warehouse Early detection using artificial intelligence and machine learning can assist in curing diseases quicker. Conclusion Data engineering in healthcare provides a plethora of opportunities.

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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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Dataversity

APRIL 5, 2021

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.

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phData

SEPTEMBER 27, 2024

Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. It’s like turning your data warehouse into a data distribution center.

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Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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Dataversity

NOVEMBER 1, 2021

Many in enterprise Data Management know the challenges that rapid business growth can present. Whether through acquisition or organic growth, the amount of enterprise data coming into the organization can feel exponential as the business hires more people, opens new locations, and serves new customers. The enterprise […].

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phData

NOVEMBER 9, 2023

The primary objective of this idea is to democratize data and make it transparent by breaking down data silos that cause friction when solving business problems. What Components Make up the Snowflake Data Cloud? What Components Make up the Snowflake Data Cloud? What is a Cloud Data Warehouse?

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