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Establishing Connections and Putting an End to Data Silos

Dataversity

They must connect not only systems, data, and applications to each other, but also to their […]. The post Establishing Connections and Putting an End to Data Silos appeared first on DATAVERSITY.

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Democratizing data for transparency and accountability

Dataconomy

While data democratization has many benefits, such as improved decision-making and enhanced innovation, it also presents a number of challenges. From lack of data literacy to data silos and security concerns, there are many obstacles that organizations need to overcome in order to successfully democratize their data.

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Improving Data Pipelines with DataOps

Dataversity

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 […].

DataOps 59
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Exploring the fundamentals of online transaction processing databases

Dataconomy

But the true power of OLTP databases lies beyond the mere execution of transactions, and delving into their inner workings is to unravel a complex tapestry of data management, high-performance computing, and real-time responsiveness. An OLAP database may also be organized as a data warehouse.

Database 159
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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

This article endeavors to alleviate those confusions. While traditional data warehouses made use of an Extract-Transform-Load (ETL) process to ingest data, data lakes instead rely on an Extract-Load-Transform (ELT) process. This adds an additional ETL step, making the data even more stale.

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Democratizing data for transparency and accountability

Dataconomy

While data democratization has many benefits, such as improved decision-making and enhanced innovation, it also presents a number of challenges. From lack of data literacy to data silos and security concerns, there are many obstacles that organizations need to overcome in order to successfully democratize their data.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. 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.

ETL 59