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7 Reasons Why Companies Should Apply DevOps and CI/CD Practices to Their Data Pipelines

Agile experimentation is the new standard in the software development landscape. Organizations aim for releasing the best version of their products as quickly as possible. DevOps and principles of continuous integration and continuous delivery/deployment (CI/CD) prepare them for a quick software release while maintaining security, quality, and compliance. 

DevOps and CI/CD practices facilitate agile software development. Recently, they have embraced transformative technologies like AI to remove the barrier between development (Dev) and operations (Ops), accelerating deployment cycles and software delivery. 

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Some Essential Features of Data Mapping

The world is being ruled by data. In the current disruptive era, enterprises around the world are dealing with ever-increasing, highly complex, bidirectional data. To enable the smooth migration of data between myriad data sources and deliver value, organizations must employ effective data transformation strategies for better insight delivery and ultimately decision-making. This is easier said than done, however. 

Data has multiple formats, languages, and schemas, and analyzing this highly complex data to extract insights and make decisions is challenging. For this, organizations need to integrate all the data sources – and thus all the data. Data mapping has a huge role to play here. 

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Data Fabrics Modernize Existing Data Management

Introduction

Data management agility takes precedence among organizations with diverse, distributed, and disruptive environment. It is one of the most crucial deciding factors in determining a company’s potential to transform data into opportunities. But managing data remains an uphill climb thanks to advancements in big data and the Internet of Things (IoT). 

Data management is susceptible to errors and delays that can impact operational efficiency and value generation. Problems aggravate when traditional data management practices are used—and the overall performance of a company hits the skids. 

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Learn How Data Mapping Supports Data Transformation and Data Integration

Data mapping is an essential component of data processes. One error in data mapping can cause ripples in the organization, bringing it to ruins through replicated errors and inaccurate analysis. So, if you fail to understand the significance of data mapping or how it’s implemented, you are minimizing the chances of your business becoming a success. 

In this article post, you’ll become aware of what data mapping is and how it can be done.

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Things to Understand Before Implementing ETL Tools

Data warehouses, databases, data lakes, or data hubs have become key growth drivers for technology-driven businesses of all sizes. There are several factors that contribute to the successful building and management of each of these data systems. The ETL (Extract, Transform, Load) strategy is the most important of them all. Nowadays, there are several best ETL tools in the market which allow businesses to design robust data systems. They are differentiated into open source and enterprise ETL tools on the basis of their implementation. This post is not focused on the best ETL tools in the market, nor does it compare ETL tools. What should you expect then? This post intends to build your understanding of the ETL processing and parameters to be checked before investing in an ETL tool.

Understanding the Basics of the ETL Processing

When developing a database, it becomes important to prepare and store data in comprehensible formats. ETL comprises three distinct functions (Extract, Transform, and Load) that are integrated in a single tool, which aids in the data preparation and storage required for database management.