Monte Carlo

JUNE 6, 2023

Sure, data quality is everyones’ problem. But who is responsible for data quality? Given the variations in approach and mixed success, we have a lot of natural experiments from which to learn. Some organizations will attempt to diffuse the responsibility widely across data stewards, data owners, data engineering and governance committees, each owning a fraction of the data value chain.

Data Governance 98

Data Governance Government Data Data Engineering 98

Cloudyard

JUNE 6, 2023

Read Time: 2 Minute, 39 Second During this post we will discuss a simple scenario using AWS Glue and Snowpark. Since long time I was planning to start and learn Snowpark and has come up with this simple and basic use-case to implement Glue and Snowpark in one pipeline. As per the requirement source system has fed a CSV file to our S3 bucket which needs to be ingested into Snowflake.

Data Ingestion 94

Data Ingestion AWS Data Big Data 94

databricks

JUNE 6, 2023

Announcing a new portfolio of Generative AI learning offerings on Databricks Academy Enroll in the Large Language Models: Application through Production on Databricks.

Portfolio 97

Portfolio Machine Learning 97

KDnuggets

JUNE 6, 2023

From image classification to chatbot therapy.

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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?

Data

Monte Carlo

JUNE 6, 2023

Generative AI is taking the world by storm – here’s what it means for data engineering and why data observability is critical for this groundbreaking technology to succeed. Maybe you’ve noticed the world has dumped the internet, mobile, social, cloud and even crypto in favor of an obsession with generative AI. But is there more to generative AI than a fancy demo on Twitter?

Data Engineering 84

Data Engineering Data Engineer Engineering Business Intelligence 84

KDnuggets

JUNE 6, 2023

Check out our latest cheat sheet! Learn how to leverage ChatGPT for data science interview preparation.

Data Science 107

Data Science Data Machine Learning 107

KDnuggets

JUNE 6, 2023

Mastering Feature Selection: An Exploration of Advanced Techniques for Supervised and Unsupervised Machine Learning Models.

Machine Learning 100

Machine Learning 100

databricks

JUNE 6, 2023

The Media & Entertainment industry is in the midst of a revolution centered around data and putting consumers at the center of every.

Entertainment 76

Entertainment Media Data 76

Hevo

JUNE 6, 2023

Data preparation is generally the most difficult, expensive, and time-consuming task in a typical analytics project. Data sets may include fragmented and incomplete data, data with the absence of any structural consistency, etc.

BI 52

BI Data Preparation Project Data 52

databricks

JUNE 6, 2023

Apache Parquet is one of the most popular open source file formats in the big data world today. Being column-oriented, Apache Parquet allows.

Data Lake 74

Data Lake Big Data Data Data Engineering 74

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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.

Database

Precisely

JUNE 6, 2023

At Precisely’s Trust ’23 conference, Chief Operating Officer Eric Yau hosted an expert panel discussion on modern data architectures. Featured panelists included Sanjeev Mohan, Principal at SanjMo and former Gartner Research VP; Atif Salam, CxO Advisor & Enterprise Technologist at AWS; and Precisely Chief Technology Officer, Tendü Yogurtçu, Ph.D.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

ArcGIS

JUNE 6, 2023

The 2023 Esri User Conference is almost here! Check out this blog for some great insights from the data management team.

Data Management 52

Data Management Management Data 52

Lyft Engineering

JUNE 6, 2023

Discover how Lyft identified and fixed performance issues in our streaming pipelines. Background Every streaming pipeline is unique. When reviewing a pipeline’s performance, we ask the following questions: “Is there a bottleneck?”, “Is the pipeline performing optimally?”, “Will it continue to scale with increased load?” Regularly asking these questions are vital to avoid scrambling to fix performance issues at the last minute.

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Utilities Coding Python Systems 123

Ascend.io

JUNE 6, 2023

In the world of cloud computing, efficiency isn’t just about running operations faster or smoother — it’s also about achieving more with less. It’s about ensuring that the resources consumed deliver maximum value and avoid unnecessary expenditures. Understanding and controlling cloud costs is a fundamental part of how Ascend manages the cloud infrastructure of our dedicated deployment customers.

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Cloud Data Pipeline Data Ingestion Cloud Storage 52

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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.

Data Analysis

Towards Data Science

JUNE 6, 2023

Fitbit activity analysis with DuckDB Photo by Jake Hills on Unsplash Wearable fitness trackers have become an integral part of our lives, collecting and tracking data about our daily activities, sleep patterns, location, heart rate, and much more. I’ve been using a Fitbit device for 6 years to monitor my health. However, I have always found the data analysis capabilities lacking — especially when I wanted to track my progress against long term fitness goals.

Data Warehouse 94

Data Warehouse Data SQL Data Analysis 94

Rockset

JUNE 6, 2023

Rockset is a real-time search and analytics database in the cloud. One of the ways Rockset maximizes price-performance for our customers is by separately scaling compute and storage. This improves efficiency and elasticity, but is challenging to implement for a real-time system. Real-time systems such as Elasticsearch were designed to work off of directly attached storage to allow for fast access in the face of real-time updates.

Metadata 52

Metadata Datasets Architecture Algorithm 52

Cloudera

JUNE 6, 2023

Opening Increased costs and wasted resources are on the rise as software systems have moved from monolithic applications to distributed, service-oriented architectures. As a result, over the past few years, interest in observability has seen a marked rise. Observability, borrowed from its control theory context , has found a real sweet spot for organizations looking to answer the question “why,” that monitoring alone is unable to answer.

Government 70

Government Professional Services Cloud Utilities 70

Snowflake

JUNE 6, 2023

Today’s governmental and educational organizations can’t fully use the wealth of data they possess to improve citizen and student outcomes. Government agencies often deal with disparate and siloed data that can impact real-time decision-making. Securely exchanging information and collaborating on data remains an essential task in almost every agency strategy.

Education 52

Education Government Cloud Amazon Web Services 52

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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