Data Engineering Podcast

JUNE 19, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

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Rockset

APRIL 18, 2023

Join me and Rockset VP of Engineering Louis Brandy for a tech talk, From Spam Fighting at Facebook to Vector Search at Rockset: How to Build Real-Time Machine Learning at Scale , on May 17th at 9am PT/ 12pm ET. Due to these difficulties, unstructured data has remained largely underutilized. Why use vector search?

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Unstructured Data Metadata Machine Learning SQL 105

Precisely

MAY 13, 2024

If you’re in the market for a data integration solution, there are many things to consider – including the flexibility of integration solutions, the availability of a strong network of service providers, and the vendor’s reputation for thought leadership in the integration space. A notable capability that achieves this is the data catalog.

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Data Engineering Podcast

JUNE 12, 2022

Summary Building a well rounded and effective data team is an iterative process, and the first hire can set the stage for future success or failure. Trupti Natu has been the first data hire multiple times and gone through the process of building teams across the different stages of growth.

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The Modern Data Company

JANUARY 22, 2024

The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

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The Modern Data Company

JANUARY 22, 2024

The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

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Data Engineering Podcast

JULY 31, 2022

In this episode Ernie Ostic shares the approach that he and his team at Manta are taking to build a complete view of data lineage across the various data systems in your organization and the useful applications of that information in the work of every data stakeholder. Atlan is the metadata hub for your data ecosystem.

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Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Metadata layer 4. Ingestion layer 2. API layer 5.

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Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Metadata layer 4. Ingestion layer 2. API layer 5.

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Monte Carlo

MAY 31, 2022

Metadata from the data warehouse/lake and from the BI tool of record can then be used to map the dependencies between the tables and dashboards. onFailure(funcName, qe, exception)) } } Spline provided a head-start in building Spark lineage. A good engineer can build solutions for hard problems. here’s why it doesn’t work.

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Snowflake

NOVEMBER 2, 2023

And, since historically tools and commercial platforms were often designed to align with one specific architecture pattern, organizations struggled to adapt to changing business needs – which of course has implications on data architecture. With our customers, we’ve seen Conway’s Law playing out more often than not.

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Monte Carlo

AUGUST 19, 2023

A comprehensive data platform solution powers data acquisition, storage, preparation, delivery, governance, and even the robust security needs of users and applications. In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations. It depends.

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Data Engineering Podcast

NOVEMBER 27, 2022

In this episode Wes McKinney shares the ways that Arrow and its related projects are improving the efficiency of data systems and driving their next stage of evolution. Atlan is the metadata hub for your data ecosystem. Missing data? Can you describe what you are building at Voltron Data and the story behind it?

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Snowflake

NOVEMBER 29, 2023

Also, the associated business metadata for omics, which make it findable for later use, are dynamic and complex and need to be captured separately. Additionally, the fact that they need to be standardized makes the data discovery effort challenging for downstream analysis.

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Monte Carlo

AUGUST 25, 2023

One advantage of data warehouses is their integrated nature. As fully managed solutions, data warehouses are designed to offer ease of construction and operation. A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor.

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Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. Those who don’t embrace it will be left behind. John agrees. “

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Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? That’s a model worth looking at when it comes to data governance,” says Bob.

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Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? That’s a model worth looking at when it comes to data governance,” says Bob.

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Towards Data Science

APRIL 6, 2023

Principles, practices, and examples for ensuring high quality data flows Source: DreamStudio (generated by author) Nearly 100% of companies today rely on data to power business opportunities and 76% use data as an integral part of forming a business strategy. When it comes to detecting anomalies in unstructured data (e.g.,

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Cloudera

MARCH 17, 2023

I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics. ChatGPT is an excellent resource for gaining high-level insights and building awareness of any technology.

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AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Tools to build an ELT pipeline.

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Rockset

AUGUST 28, 2023

We founded Rockset to empower everyone from Fortune 500 to a five-person startup to build powerful search and AI applications and scale them efficiently in the cloud. We believe any engineer in the world should be able to quickly build powerful data apps. Building these apps should be as simple as constructing a SQL query.

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ProjectPro

FEBRUARY 8, 2023

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. being data exactly matches the classifier, and 0.0 Why Use AWS Glue?

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Monte Carlo

JANUARY 25, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. Hint: it’s not a one-size-fits-all answer, but answering a few critical questions can help. Let’s jump in!

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Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

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Snowflake

JANUARY 22, 2024

As part of that transition, Fidelity has consolidated its analytics data into its Enterprise Analytics Platform, which is engineered using the Snowflake Data Cloud, making it easier for teams and departments across the company to access the data they need. Ready to start building models of your own with Snowpark ML?

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Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

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Monte Carlo

JANUARY 24, 2023

Data fabric architecture is complex, but there are a few key components that every data fabric should include: automated metadata analysis, semantic knowledge graphs, and universal access controls. Key components of a data fabric Metadata analysis Metadata is data about your data.

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Precisely

FEBRUARY 9, 2024

Data fabrics are being explored by business and IT teams to connect data through its metadata and provide the knowledge layer required to identify the data products that will provide the most meaning and value.

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Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

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Monte Carlo

FEBRUARY 7, 2024

Right now, that includes: Code assistance: Tools like GitHub Copilot are capable of generating code in languages like Python and SQL — making it faster and easier for data engineers to build, test, maintain, and optimize pipelines. And by and large, these developments are good news for data engineers! Things break.

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Towards Data Science

AUGUST 10, 2023

3- Putting unstructured data to work All of our expert panelists were excited about the potential for generative AI to enable data teams and organizations to extract value from non-relational sources. There’s plenty of unstructured data in the world. So let’s take a look at some of the recurring themes.

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Data Engineering Podcast

SEPTEMBER 14, 2020

I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

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AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

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Cloudera

OCTOBER 7, 2021

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs.

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AltexSoft

AUGUST 22, 2022

What’s more, Gartner identifies data fabric implementation as one of the top strategic technology trends for 2022 and expects that by 2024, data fabric deployments will increase the efficiency of data use while halving human-driven data management tasks. What is data fabric? How data fabric works.

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AltexSoft

FEBRUARY 11, 2023

However, in practice, many companies don’t necessarily have data architects so there are only data engineers and this distinction won’t be applicable. The daily tasks of a data architect require more of a strategic thinking, while a data engineer’s workload is more about building the software infrastructure, which are technical tasks.

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