Start Data Engineering
SEPTEMBER 18, 2024
1. Introduction 2. Setup 3. Parts of data engineering 3.1. Requirements 3.1.1. Understand input datasets available 3.1.2. Define what the output dataset will look like 3.1.3. Define SLAs so stakeholders know what to expect 3.1.4. Define checks to ensure the output dataset is usable 3.2. Identify what tool to use to process data 3.3. Data flow architecture 3.
Jesse Anderson
SEPTEMBER 18, 2024
Survey Changes Over Time Between 2020 and 2024 (see 2020, 2023, and 2024 for each year’s information), I’ve been conducting a data teams survey. I wanted to dedicate an entire post to examining the change in data teams over time. Total Value Creation The most important question I ask each year concerns data team value creation. I break the question into two parts: “How successful would the business say your projects are?
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databricks
SEPTEMBER 18, 2024
The Databricks Generative AI Startup Challenge offers $1M+ in prizes for innovative startups building Generative AI use cases on Databricks. Apply by November 1, 2024!
Netflix Tech
SEPTEMBER 18, 2024
Vidhya Arvind , Rajasekhar Ummadisetty , Joey Lynch , Vinay Chella Introduction At Netflix our ability to deliver seamless, high-quality, streaming experiences to millions of users hinges on robust, global backend infrastructure. Central to this infrastructure is our use of multiple online distributed databases such as Apache Cassandra , a NoSQL database known for its high availability and scalability.
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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
Data Engineering Weekly
SEPTEMBER 18, 2024
Click the Link Below to Get Your Free Data Observability Buyers Guide: [link] The Buyer Guide for Data Observability is out. Please feel free to make a copy or comment to add more criteria. I w ant to extend my gratitude to the Data Heroes Community for their valuable insights and discussions, which served as the foundation for this piece. The points and thoughts shared here are largely drawn from the community's collective knowledge and contributions.
ArcGIS
SEPTEMBER 18, 2024
Learn the difference between ArcGIS Data Interoperability and FME technology and how they relate to one another.
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
databricks
SEPTEMBER 18, 2024
At Databricks, we know that data is one of your most valuable assets. Our product and security teams work together to deliver an enterprise-grade Data Intelligence Platform that enables you to defend against security risks and meet your compliance obligations. In this blog, we'll explain how you can leverage our platform's security features to establish a robust defense-in-depth posture that protects your data and AI assets from risks.
KDnuggets
SEPTEMBER 18, 2024
Heaps and heaps of new technology are entering the market, and these new tools and software are making our lives easier. However, although our day-to-day tasks have become easier, there has been an increase in the number of cyber threats. There is a need for the right people to come in and identify and mitigate.
databricks
SEPTEMBER 18, 2024
Transformer models, the backbone of modern language AI, rely on the attention mechanism to process context when generating output. During inference, the attention.
KDnuggets
SEPTEMBER 18, 2024
Versioning Best Practices for Data Science Projects As I have mentioned, this article assumes you have basic versioning knowledge. You don’t necessarily need to be adept at it, but at least you already have a Git version tool in the environment. If you haven’t, please follow the instructions for installation on the Git website.
Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
Cloudera
SEPTEMBER 18, 2024
According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making. More and more enterprises are leveraging pre-trained models for various applications, from natural language processing to computer vision.
Snowflake
SEPTEMBER 18, 2024
As the frenzied hype around generative AI cools off and as we get into the year of ideation, earlier adopters of AI are starting to see the results of initial experimentation. And these conversations are increasingly shifting to a more problem-oriented mentality. A lot of people were understandably swept up in the excitement of all that AI can do, only to find that some use cases were too risky or that those problems could be solved with traditional methods that were less costly.
Precisely
SEPTEMBER 18, 2024
Businesses around the world are facing major challenges due to higher manufacturing costs, disruptive new technologies like artificial intelligence (AI), and tougher global competition. This means it’s more important than ever to make data-driven decisions, cut costs, and improve efficiency. But this is all easier said than done, as evidenced by key findings from this year’s 2025 Outlook: Data Integrity Trends and Insights report, published in partnership between Precisely and the Center for App
DataKitchen
SEPTEMBER 18, 2024
A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. According to DataKitchen’s 2024 market research, conducted with over three dozen data quality leaders, the complexity of data quality problems stems from the diverse nature of data sources, the increasing scale of data, and the fragmented nature of data systems.
Speaker: Nikhil Joshi, Founder & President of Snic Solutions
Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.
ArcGIS
SEPTEMBER 18, 2024
Learn how to build cross-street data into a geocoding locator using ArcGIS Data Interoperability and its no-code approach.
Yelp Engineering
SEPTEMBER 18, 2024
Machine Learning Feature Stores ML Feature Store at Yelp Many of Yelp’s core capabilities such as business search, ads, and reviews are powered by Machine Learning (ML). In order to ensure these capabilities are well supported, we have built a dedicated ML platform. One of the pillars of this infrastructure is the Feature Store, which is a centralized data store for ML Features that are the input of ML models.
Confluent
SEPTEMBER 18, 2024
Jump-start a new use case or accelerate your migration journey with our new Build with Confluent and Confluent Migration Accelerator partners.
KDnuggets
SEPTEMBER 18, 2024
Sponsored Content “Completing the program has provided me with proficiency in essential data science methodologies and programming languages, including R, Python, SQL, and Tableau. Additionally, the program's flexibility allowed me to select project subjects aligned with my interests, fostering hands-on learning experiences. Through these projects, I gained practical experience applying a diverse.
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.
Monte Carlo
SEPTEMBER 18, 2024
How do you know if data is fit for use? While it will vary a bit depending on the use case, there are six dimensions of data quality that have become a standard best practice for this type of evaluation. Let’s take a look at each of these dimensions and see how any member of the data team can deploy a relevant monitor using the extensible Monte Carlo data observabilit y platform.
Knowledge Hut
SEPTEMBER 18, 2024
Ethical hackers are in high demand by companies and organizations that need to protect their data and systems from malicious activity. As cybercrime continues to evolve and become more sophisticated, companies need people with the skills and knowledge to outsmart cyber criminals. In 2024 and the upcoming years, the demand for ethical hackers will be higher, so now is the time to start preparing for a career in this exciting field.
Knowledge Hut
SEPTEMBER 18, 2024
As the world economy continues to globalize, the project management demand is expected to grow rapidly. A project manager is responsible for ensuring a project is completed on time, within budget, and to the required standard. To be successful in this role, a project manager must have excellent organizational and communication skills. They must be able to work effectively with a team of people, as well as be able to take up the role of a leader whenever necessary.
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