Dataversity

SEPTEMBER 24, 2021

We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 The reason is pretty obvious – businesses want to leverage the power of data […].

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Dataversity

DECEMBER 11, 2023

Organizations learned a valuable lesson in 2023: It isn’t sufficient to rely on securing data once it has landed in a cloud data warehouse or analytical store. As a result, data owners are highly motivated to explore technologies in 2024 that can protect data from the moment it begins its journey in the source systems.

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Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The post A Bridge Between Data Lakes and Data Warehouses appeared first on DATAVERSITY.

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Smart Data Collective

OCTOBER 27, 2021

Interactive analytics applications make it easy to get and build reports from large unstructured data sets fast and at scale. In this article, we’re going to look at the top 5. Firebolt makes engineering a sub-second analytics experience possible by delivering production-grade data applications & analytics. Google BigQuery.

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Analytics Vidhya

OCTOBER 25, 2023

Introduction Struggling with expanding a business database due to storage, management, and data accessibility issues? To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023.

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Dataversity

MARCH 2, 2022

Without effective and comprehensive validation, a data warehouse becomes a data swamp. With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical.

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Dataversity

AUGUST 5, 2021

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

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Dataversity

NOVEMBER 29, 2021

There’s been a lot of talk about the modern data stack recently. Much of this focus is placed on the innovations around the movement, transformation, and governance of data as it relates to the shift from on-premise to cloud data warehouse-centric architectures.

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Alation

JANUARY 17, 2023

In this article, I will explain the modern data stack in detail, list some benefits, and discuss what the future holds. What Is the Modern Data Stack? The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform.

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Dataversity

FEBRUARY 7, 2022

Data paradigms are changing. The concept of a data warehouse as the only solution for integrating data sources should be questioned. This approach is increasingly at odds with the realities of how data is transacted and used in enterprises. Instead of a few data sources, there can be 20, 30, 40, even more.

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Alation

JULY 13, 2021

The Data Race to the Cloud. This recent cloud migration applies to all who use data. We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment.

Cloud Data 52

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Mlearning.ai

FEBRUARY 16, 2023

The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency.

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phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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The MLOps Blog

MAY 17, 2023

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. Focus Area ETL helps to transform the raw data into a structured format that can be easily available for data scientists to create models and interpret for any data-driven decision.

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Precisely

JANUARY 25, 2024

Many organizations adopt a long-term approach, leveraging the relative strengths of both mainframe and cloud systems. This integrated strategy keeps a wide range of IT options open, blending the reliability of mainframes with the innovation of cloud computing.

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IBM Journey to AI blog

JULY 17, 2023

sales conversation summaries, insurance coverage, meeting transcripts, contract information) Generate: Generate text content for a specific purpose, such as marketing campaigns, job descriptions, blogs or articles, and email drafting support. The post Exploring the AI and data capabilities of watsonx appeared first on IBM Blog.

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ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

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Dataversity

NOVEMBER 25, 2022

At the same time, many forward-thinking businesses, from startups to large corporations, have implemented a modern cloud analytics stack to use data more efficiently. In this article, we will discuss how a modern […].

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Pickl AI

OCTOBER 15, 2024

The right ETL platform ensures data flows seamlessly across systems, providing accurate and consistent information for decision-making. Effective integration is crucial to maintaining operational efficiency and data accuracy, as modern businesses handle vast amounts of data. What is ETL in Data Integration?

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Mlearning.ai

JULY 10, 2023

And since the advent of cloud data warehouse, I was lucky enough to get a good amount of exposure on Google Cloud Platform in the early stages of the era which became my competitive edge in this wild job market. A lot of you who are already in the data science field must be familiar with BigQuery and its advantages.

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Dataversity

SEPTEMBER 6, 2021

The rush to become data-driven is more heated, important, and pronounced than it has ever been. Businesses understand that if they continue to lead by guesswork and gut feeling, they’ll fall behind organizations that have come to recognize and utilize the power and potential of data. Click to learn more about author Mike Potter.

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Dataversity

SEPTEMBER 11, 2023

Organizations have become highly data-centric in the past years, increasing complications and costs as the volume of data rose. However, data integrity issues alone cost organizations $12.9 million annually, on average, according to Gartner.

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Dataversity

MARCH 22, 2021

This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]. The post Where Is the Data Technology Industry Headed? Click here to learn more about Heine Krog Iversen.

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Dataversity

AUGUST 26, 2022

It’s as fundamental to business operations as you can get – if the margin isn’t there, you’re not going to have a viable business, and in an increasingly data-driven world, businesses that […].

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Dataversity

APRIL 5, 2021

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.

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Dataversity

OCTOBER 11, 2021

Click to learn more about author Joan Fabregat-Serra. IT has weaponized jargon since the very beginning of IT itself. Jargon was a key element to create vendor lock-in situations during the ’90s and early 2000s. Moreover, complex usability helped in developing a network of certified (aka expensive and lucrative) consultancy workforce.

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Alation

AUGUST 11, 2021

Anthony and his governance team use data to uncover customer insights, and to discover areas where they can improve safety. Like many organizations, TMIC had a complex set of data sources and internal data warehouses. This human-centric approach surfaces key data details, like query logs, to show how your data is used.

Data Governance 52

Data Governance Data Warehouse Data Classification Cloud Data 52

ODSC - Open Data Science

JULY 11, 2023

6] Questions for AI About Data Centers To learn more about data centers I began by asking ChatGPT what Chief Transformation Officers should know about them. This interaction is described in my upcoming article in CXOTech Magazine. Next, I asked what a data center typically looks like and how it should be staffed.

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phData

JUNE 14, 2023

Figure-02 - Imperative Vs. Declarative Database Change Management Approaches For insights into database change management tool selection for Snowflake, check out this article. These objects include integration objects, tables, stages, pipes, tasks, streams, stored procedures, and more.

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Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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Alation

FEBRUARY 8, 2022

Are they just for this season, or an article you can rely on for life? Now let’s apply the same principles to data. Data observability — comprising identifying, troubleshooting, and resolving data issues — can be achieved through quality testing built by teams within each domain. Quality of the product. Levi’s, etc.)

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Alation

JANUARY 25, 2022

On the policy front, a feature like Policy Center empowers users to enforce and track policies at scale; this ensures that people use data compliantly, and organizations are prepared for compliance audits. How can data users navigate and understand such a complex landscape predictably?

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Dataversity

FEBRUARY 16, 2022

The semantic layer concept within the data stack is not new but is an increasingly popular topic of conversation. I predict that in 2022, we’ll see mainstream awareness of the semantic layer, especially as enterprises begin to see real-world examples of its benefits.

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Data Lakes Data Warehouse Cloud Data Analytics 52

Dataversity

FEBRUARY 8, 2022

Every generation of data infrastructure technology has promised more speed and agility, or better standardization, centralization, and control.

Data Lakes 52

Data Lakes Data Warehouse Database Cloud Data 52

Dataversity

AUGUST 6, 2021

This has been accompanied by a concurrent data explosion, with every industry sector now generating information […]. Click to learn more about author Sudeep Rao.

Data Science 52

Data Science Data Warehouse Data Engineering Data Engineer 52

Dataversity

MAY 17, 2021

There are advantages and disadvantages to both ETL and ELT. To understand which method is a better fit, it’s important to understand what it means when one letter comes before the other. The post Understanding the ETL vs. ELT Alphabet Soup and When to Use Each appeared first on DATAVERSITY.

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Dataversity

MARCH 17, 2021

I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]. The post Is Lakehouse Architecture a Grand Unification in Data Analytics?

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