Fri.May 03, 2024

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A Notebook is all I want or Don't

Data Engineering Weekly

The tweet received strong reactions on LinkedIn and Twitter. To clarify, I quoted it as a Notebook-style development, but it is not exactly a Notebook. There is a lot of context missing in that tweet, so I decided to write a blog about it. People have reservations about using tools like Jupytor Notebook for the production pipeline for a good reason.

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Executive Overview: The Rise of Open Foundational Models

databricks

Moving generative AI applications from the proof of concept stage into production requires control, reliability and data governance. Organizations are turning to open.

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5 Simple Steps to Automate Data Cleaning with Python

KDnuggets

Automate your data cleaning process with a practical 5-step pipeline in Python, ideal for beginners.

Python 140
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Modeling Slowly Changing Dimensions

Towards Data Science

A deep dive into the various SCD types and how they can be implemented in Data Warehouses Continue reading on Towards Data Science »

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

Executive leaders and board members are pushing their teams to adopt Generative AI to gain a competitive edge, save money, and otherwise take advantage of the promise of this new era of artificial intelligence. There's no question that it is challenging to figure out where to focus and how to advance when it’s a new field that is evolving everyday. 💡 This new webinar featuring Maher Hanafi, CTO of Betterworks, will explore a practical framework to transform Generative AI prototypes into

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Migrate Azure Postgres to Redshift: Maximize Data Performance

Hevo

Insights generation from in-house data has become one of the most critical steps for any business. Integrating data from a database into a data warehouse enables companies to obtain essential factors influencing their operations and understand patterns that can boost business performance.

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How BI Can Inform Your ERP Selection Process (Manufacturing)

FreshBI

For businesses that derive their revenue from Manufacturing or Distribution, the choice for ERP includes MS Dynamics 365 Biz Central, SAP Biz One Pro, SYSPRO, Netsuite, Acumatica. The purpose of this blog is to provide an example of how a manufacturing operation can use Business Intelligence (BI) anchored in its economic engine, to inform the ERP selection process.

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Enterprise Data Quality: 3 Quick Tips from Data Leaders

Monte Carlo

It’s 2024, and the data estate has changed. Data systems are more diverse. Architectures are more complex. And with the acceleration of AI, that’s not changing any time soon. But even though the data landscape is evolving, many enterprise data organizations are still managing data quality the “old” way: with simple data quality monitoring. The basics haven’t changed: high-quality data is still critical to successful business operations.

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Azure MySQL to Redshift: Optimizing Data Warehousing Capabilities

Hevo

Imagine you are managing a rapidly growing e-commerce platform. That platform generates a large amount of data related to transactions, customer interactions, product details, feedback, and more. Azure Database for MySQL can efficiently handle your transactional data.

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Dynamic Merge Procedure: Snowflake’s Enhanced Flexibility

Cloudyard

Read Time: 1 Minute, 32 Second Last week, I introduced a stored procedure called DYNAMIC_MERGE , which dynamically retrieved column names from a staging table and used them to construct a MERGE INTO statement. While this approach offered flexibility, it had a limitation – the HASH condition used static column names. Hence relying on static column names, limiting the procedure’s adaptability across different tables.

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Azure MySQL to Snowflake: 2 Efficient Data Migration Methods

Hevo

In today’s digital era, businesses continually look for ways to manage their data assets. Azure Database for MySQL is a robust storage solution that manages relational data. However, as your business grows and data becomes more complex, managing and analyzing it becomes more challenging. This is where Snowflake comes in.

MySQL 52
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Leading the Development of Profitable and Sustainable Products

Speaker: Jason Tanner

While growth of software-enabled solutions generates momentum, growth alone is not enough to ensure sustainability. The probability of success dramatically improves with early planning for profitability. A sustainable business model contains a system of interrelated choices made not once but over time. Join this webinar for an iterative approach to ensuring solution, economic and relationship sustainability.

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Top Features of Power BI

Knowledge Hut

Power BI is a business analytics service by Microsoft that provides users with Data Visualization and Business Intelligence tools with an elementary interface, simple for end-users so that they create reports and dashboards of their own. Microsoft Power BI Course helps to find insights within the data of an organisation. It converts data from various data sources to interactive BI reports and dashboards, like it forms different data models, creates graphs and charts which depict visuals of the d

BI 52
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The Ultimate Guide to Master Snowflake Data Lineage

Hevo

If your organization is data-driven, it is important to understand your data’s origin, movement, and transformation. This imparts transparency within your organization, ensures data integrity, and enables informed decision-making. You can use data lineage for this.

Data 52
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What is Bias-Variance Tradeoff in Machine Learning

Knowledge Hut

What is Machine Learning? Machine Learning is a multidisciplinary field of study, which gives computers the ability to solve complex problems, which otherwise would be nearly impossible to be hand-coded by a human being. Machine Learning is a scientific field of study which involves the use of algorithms and statistics to perform a given task by relying on inference from data instead of explicit instructions.

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Data Quality Monitoring: A Guide to Ensure Data Integrity

Hevo

Most organizations today practice a data-driven culture, emphasizing the importance of evidence-based decisions. You can also utilize the data available about your organization to perform various analyses and make data-informed decisions, contributing towards sustainable business growth.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Overfitting and Underfitting in Machine Learning + [Example]

Knowledge Hut

There have been many articles written regarding overfitting and underfitting in machine learning, but virtually all of them are merely a list of tools. "Top 10 tools for dealing with overfitting and underfitting," or "best strategies: how to avoid overfitting in machine learning" or "best strategies: how to avoid underfitting in machine learning." It's like being shown nails but not being told how to hammer them.

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Meta’s New Data Analyst Professional Certification Has Dropped!

KDnuggets

Start a new career with Meta’s Data Analyst Certification and be job-ready in 5 months or less!

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K-Nearest Neighbor (KNN) Algorithm for Machine Learning

Knowledge Hut

If you are thinking of a simple, easy-to-implement supervised machine learning algorithm that can be used to solve both classifications as well as regression problems, K-Nearest Neighbors (K-NN) is a perfect choice. Learning K-Nearest Neighbors is a great way to introduce yourself to machine learning and classification in general. If you explore machine learning with Python syllabus , you will realize the extent of the application of KNN.

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Data Migration from AWS RDS Oracle to Redshift: 2 Efficient Methods

Hevo

Cloud solutions like AWS RDS for Oracle offer improved accessibility and robust security features. However, as data volumes grow, analyzing data on the AWS RDS Oracle database through multiple SQL queries can lead to inconsistency and performance degradation.

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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ASP.NET VS PHP

Knowledge Hut

ASP.NET and PHP are pretty popular languages in the programming world used by a huge number of developers and this makes it difficult for the new developers to choose either one of them. The comparison between these two has been in debate in recent times. Both of these languages are used in large web-based applications. Some successful companies like Google, Facebook, and Twitter, etc, also use these languages.

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AWS RDS Oracle to Databricks: Strategic Data Migration Methods

Hevo

While AWS RDS Oracle offers a robust relational database solution over the cloud, Databricks simplifies big data processing with features such as automated scheduling and optimized Spark clusters. Integrating data from AWS RDS Oracle to Databricks enables you to handle large volumes of data within a collaborative workspace to derive actionable insights in real-time.

AWS 40
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Fundamentals of Apache Spark

Knowledge Hut

Introduction Before getting into the fundamentals of Apache Spark, let’s understand What really is ‘Apache Spark’ is? Following is the authentic one-liner definition. Apache Spark is a fast and general-purpose, cluster computing system. One would find multiple definitions when you search the term Apache Spark. All of those give similar gist, just different words.

Scala 98
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Data Quality Management Techniques and Best Practices

Hevo

Many organizations today heavily rely on data to make business-related decisions. Data is an invaluable asset that helps you substantiate your convictions with evidence and facilitates stakeholder buy-in. However, ensuring your data is of high quality is paramount as it directly correlates to the accuracy of the desired results.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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How to use sorted() and sort() in Python 3

Knowledge Hut

Whenever you visit a pharmacy and ask for a particular medicine, have you noticed something? It hardly takes any time for the pharmacist to find it among several medicines. This is because all the items are arranged in a certain fashion which helps them know the exact place to look for. They may be arranged in alphabetical order or according to their category such as ophthalmic or neuro or gastroenterology and so on.

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A Guide to Effective Data Cleaning Tools in Python

Hevo

The quality of your data analysis and the insights derived directly depends on the quality of the data you feed. This is why data cleaning is crucial in ensuring your datasets are accurate, consistent, and reliable for further analysis.

Python 40
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Apache Kafka Vs Apache Spark: Know the Differences

Knowledge Hut

A new breed of ‘Fast Data’ architectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. - Dean Wampler (Renowned author of many big data technology-related books) Dean Wampler makes an important point in one of his webinars. The demand for stream processing is increasing every day in today’s era.

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Azure Postgres to Databricks: 2 Extensive Data Migration Methods

Hevo

Most businesses face a significant challenge in efficiently managing and extracting insights from disparate data. Azure Postgres offers a robust storage solution but needs built-in tools for performing complex analytics tasks, like building machine learning models. This is where Databricks comes in.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Decision Tree Algorithm in Machine Learning: Types, Examples

Knowledge Hut

Machine Learning is an interdisciplinary field of study and is a sub-domain of Artificial Intelligence. It gives computers the ability to learn and infer from a huge amount of homogeneous data, without having to be programmed explicitly. Before dwelling on this article, let's know more about r squared meaning here. Types of Machine Learning: Machine Learning can broadly be classified into three types: Supervised Learning: If the available dataset has predefined features and labels, on which

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2 Easy Methods to Integrate Azure Postgres to BigQuery

Hevo

PostgreSQL, also known as Postgres, is an advanced object-relational database management system (ORDBMS) used for data storage, retrieval, and management. It is available on the Azure platform in a PaaS model (Platform as a Service) through the Azure Database for PostgreSQL service. Azure Postgres automates several tasks related to relational databases.

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Agile Coach vs Scrum Master: The Difference Stated

Knowledge Hut

Agile methodology is a simple, flexible, and iterative product development model with the distinct advantages of accommodating new requirement changes and incorporating the feedback of the previous iterations over the traditional waterfall development model. Agile methodology is the most popular and dynamic software product development and project maintenance model.

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Point to Point Data Integration vs Cloud Data Integration: 4 Critical Differences

Hevo

You need data integration for simplified data analytics. Given how siloed data sources have gotten with the evolution of the modern data stack, it’s become even more important to bring data from multiple disparate sources to a central repository. Now, there are various methods to execute data integration between two applications.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.