Data Engineering Podcast

OCTOBER 26, 2020

If you are putting your workflows into production, then you need to consider how you are going to implement data security, including access controls and auditing. Different databases and storage systems all have their own method of restricting access, and they are not all compatible with each other.

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Knowledge Hut

JANUARY 3, 2024

Cloud Computing is a revolutionary technology transforming enterprises and accelerating digital transformation. It is said that more businesses around the world will increase their investments in Cloud technology solutions, and there has been a sudden spike in Cloud deployments ever since the COVID-19 pandemic started.

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Cloudera

OCTOBER 19, 2022

The telecommunications industry continues to develop hybrid data architectures to support data workload virtualization and cloud migration. With multiple speaking tracks focusing on technology, networks, and data & AI, industry leaders repeatedly highlighted the hybrid nature of their infrastructure. .

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Cloudera

APRIL 18, 2024

More Businesses Are Taking a Holistic Approach to Data Strategy One of the more common trends we saw coming up through conversations during the summit was the need for a reframing of how we approach data strategy—taking a much more holistic viewpoint to it than organizations otherwise would have in past years.

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Cloudera

FEBRUARY 4, 2021

I am pleased to announce that Cloudera was just named the Risk Data Repository and Data Management Product of the Year in the Risk Markets Technology Awards 2021. . Supporting the industry’s risk data depository and data management needs. End-to-end Data Lifecycle. Shared Data Experience (SDX).

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Cloudera

NOVEMBER 1, 2022

In the private sector, excluding highly regulated industries like financial services, the migration to the public cloud was the answer to most IT modernization woes, especially those around data, analytics, and storage. It’s here where the private cloud delivers.

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Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

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Data Integration Metadata Amazon Web Services Data Governance 52

Snowflake

APRIL 29, 2024

ICT Risk Management Framework and Governance FEs’ leadership teams must define a risk management strategy, inclusive of both their internally managed critical systems and the risks associated with their ICT providers. This prioritizes security measures and simplifies data discovery. How can Snowflake Help?

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Transportation Data Governance Government Consulting 83

Snowflake

FEBRUARY 27, 2023

The final elements of the ManoMano data strategy are ML and data science, which encompass aspects such as categorization, automated extraction of product specifications, product recommendations and cross-selling. Data governance issues can then be addressed. What’s the SLA?

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Snowflake

FEBRUARY 1, 2023

The resulting report, How to Win in the Data Economy , includes anecdotes from dozens of customers, analysts, and influencers about how to succeed, all in addition to the survey itself, based on feedback from 1,000 senior business, technology, and data managers across five industries and from all over the world.

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dbt Developer Hub

JULY 2, 2023

Due to its complexity, Data Vault is not a go-to choice for: Simple and constant systems; Quick one-off solutions for experiments or short-term data warehouse projects; Data warehouse layers needed for direct reporting. Auditable data ​ One of the main selling points of Data Vault is its auditability.

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Knowledge Hut

MARCH 28, 2024

Data Engineer Career: Overview Currently, with the enormous growth in the volume, variety, and veracity of data generated and the will of large firms to store and analyze their data, data management is a critical aspect of data science. That’s where data engineers are on the go.

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Cloudera

JUNE 22, 2023

The stringent requirements imposed by regulatory compliance, coupled with the proprietary nature of most legacy systems, make it all but impossible to consolidate these resources onto a data platform hosted in the public cloud. Simplified compliance. Flexibility. A radically improved security posture.

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Precisely

JANUARY 9, 2023

More sophisticated data initiatives will increase data quality challenges Data quality has always been a top concern for businesses, but now the use cases for it are evolving. As data initiatives become more sophisticated, organizations will uncover new data quality challenges.

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Cloudera

JUNE 27, 2023

A modern data architecture can provide the foundation for real-time visibility into the health of telecom networks, enabling telcos to rapidly diagnose and resolve service issues and boost operational efficiency. Offload data from legacy, on-premises analytic platforms and appliances. Simplify, and where possible, automate governance.

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Databand.ai

JULY 19, 2023

Data lineage tools are not a new concept. However, their importance has grown significantly in recent years due to the increasing complexity of data architectures and the growing need for data governance and compliance. In this article: Why Are Data Lineage Tools Important?

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Cloudera

OCTOBER 26, 2020

Just like when it comes to data access in business. Enabling data access for end-users so they can drive insight and business value is a typical area of compromise between IT and users. Data access can either be very secure but restrictive or very open yet risky. Quickly onboard data.

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Databand.ai

JUNE 21, 2023

Accurate and consistent data enables organizations to gain insights, identify trends, and make data-driven decisions that drive growth. Data integrity tools are also crucial for regulatory compliance. These tools include Informatica Data Quality, Informatica Master and Data Management.

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Snowflake

MARCH 21, 2023

In February, Snowflake launched new features around streaming data ingestion and data governance and improved SQL experience and performance, with enhancements to Search Optimization Service and more. It also offers cloud consulting services with 20+ years of experience serving small businesses and Fortune 500 companies.

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Precisely

MAY 31, 2023

When attempting to build a data strategy, the primary obstacle organizations face is a lack of resources. Teams are building complex, hybrid, multi-cloud environments, moving critical data workloads to the cloud, and addressing data quality challenges.

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Ascend.io

SEPTEMBER 5, 2023

In the fast-evolving landscape of cloud data solutions, Snowflake has consistently been at the forefront of innovation, offering enterprises sophisticated tools to optimize their data management. This is crucial for organizations that use both SQL and Python for data processing and analysis.

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Snowflake

FEBRUARY 5, 2024

The foundation for success is a data platform that allows flexible, cost-effective ways to access gen AI — whether organizations want to use off-the-shelf commercial and open-source large language models (LLMs), or fine-tune their own LLMs for more complex applications. They’ll prioritize data solutions that work across clouds.

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Knowledge Hut

APRIL 23, 2024

Privacy is another grave issue, especially on social media where extremely sensitive personal data is shared and stored. Also, IoT devices make 24/7 access easy but pose some level of danger to data without 2-step verification and end-to-end encryption. Costs Every activity related to big data brings significant costs.

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Data Engineering Podcast

NOVEMBER 9, 2020

He also shares the internal architecture, how he approached the design to make it accessible and easy to use, and how it autodiscovers the schemas and metadata for your source systems. Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance?

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Data Engineering Podcast

DECEMBER 14, 2020

This was a great conversation about real world experiences in building a successful data-oriented business. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering?

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Data Engineering Podcast

SEPTEMBER 28, 2020

To make the benefits of the Kafka ecosystem more accessible and reduce the operational burden, Alexander Gallego and his team at Vectorized created the Red Panda engine. This was a fascinating conversation with an energetic and enthusiastic engineer and founder about the challenges and opportunities in the realm of streaming data.

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Data Engineering Podcast

NOVEMBER 2, 2020

In this episode Einat Orr and Oz Katz explain how they implemented branching and merging capabilities for object storage, best practices for how to use versioning primitives to introduce changes to your data lake, how LakeFS is architected, and how you can start using it for your own data platform.

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Data Engineering Podcast

DECEMBER 7, 2020

If you are struggling to deliver value from big data, or just starting down the path of building the organizational capacity to turn raw information into valuable products then this is a conversation that you don’t want to miss. If you hand a book to a new data engineer, what wisdom would you add to it?

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Data Engineering Podcast

OCTOBER 12, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it?

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Business Intelligence BI Consulting Data Ingestion 100

Data Engineering Podcast

SEPTEMBER 21, 2020

This was a useful conversation for anyone working with data who has found themselves spending too much time chasing the latest trends and wishes to develop a more focused approach to their work. If you hand a book to a new data engineer, what wisdom would you add to it? Which ones are you happy about?

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Data Engineering Podcast

OCTOBER 19, 2020

They also discuss methods for gaining visibility into the flow of data through your infrastructure, how to diagnose and prevent potential problems, and what they are building at Monte Carlo to help you maintain your data’s uptime. If you hand a book to a new data engineer, what wisdom would you add to it?

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Data Engineering Podcast

OCTOBER 5, 2020

In this episode founders DeVaris Brown and Ali Hamidi explain how their tenure at Heroku informed their approach to making data integration self service, how the platform is architected, and how they have designed their system to adapt to the continued evolution of the data ecosystem. What do you have planned for the future?

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Knowledge Hut

NOVEMBER 2, 2023

MS BI offers a comprehensive solution for data management and reporting, thanks to its powerful tools like SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), and SQL Server Reporting Services (SSRS). Power BI: Power BI is often cloud-based.

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Precisely

JANUARY 17, 2023

Data integrity trends for 2023, has agility toping the list of success factors for most firms, as business leaders focus on rapid time to value and an emphasis on responding quickly to emerging opportunities and threats. With these goals in mind, access to accurate, consistent, and contextual information is critical.

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Data Engineering Podcast

FEBRUARY 24, 2020

Summary Misaligned priorities across business units can lead to tensions that drive members of the organization to build data and analytics projects without the guidance or support of engineering or IT staff. The availability of cloud platforms and managed services makes this a viable option, but can lead to downstream challenges.

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AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. This privacy law must be kept in mind when building data architecture.

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Precisely

MARCH 14, 2023

But early adopters realized that the expertise and hardware needed to manage these systems properly were complex and expensive. First, private cloud infrastructure providers like Amazon (AWS), Microsoft (Azure), and Google (GCP) began by offering more cost-effective and elastic resources for fast access to infrastructure.

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