phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineering 195

Data Engineering Data Engineer Data Engineering Data Engineering 195

IBM Journey to AI blog

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lakes 61

Data Lakes Data Warehouse Data Governance SQL 61

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lakes 52

Data Lakes Data Governance Data Warehouse Business Intelligence 52

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Modern businesses are increasingly leveraging analytics for a range of use cases. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. What is Data Analytics?

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

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Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

NOVEMBER 9, 2023

The main goal of a data mesh structure is to drive: Domain-driven ownership Data as a product Self-service infrastructure Federated governance One of the primary challenges that organizations face is data governance. What is a Cloud Data Warehouse? What is a Data Lake?

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Data Warehouse Data Lakes Clustering Cloud Data 98

Precisely

OCTOBER 16, 2023

Rapid advancements in digital technologies are transforming cloud-based computing and cloud analytics. Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. In a connected mainframe/cloud environment, data is often diverse and fragmented.

Analytics 70

Analytics Analytics Big Data Analytics Big Data Analytics 70

IBM Journey to AI blog

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 87

Data Warehouse Data Lakes Cloud Data Analytics 87

IBM Journey to AI blog

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Data Warehouse 56

Data Warehouse Data Engineering Data Engineer Data Engineering 56

phData

APRIL 29, 2024

In our previous blog, Top 5 Fivetran Connectors for Financial Services , we explored Fivetran’s capabilities that address the data integration needs of the finance industry. Now, let’s cover the healthcare industry, which also has a surging demand for data and analytics, along with the underlying processes to make it happen.

SQL 52

SQL Azure Data Warehouse Cloud Data 52

IBM Journey to AI blog

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Lakes 59

Data Lakes AI AI Data Governance 59

phData

MAY 13, 2024

There are many challenges to overcome when doing this, and understanding them and choosing the right solutions is critical to the ultimate success and enablement of better decision-making using your ERP data. Breaking free from the constraints of legacy SAP systems creates a strategic advantage for your organization.

Database 52

Database Analytics Analytics Machine Learning 52

ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. They all agree that a Datamart is a subject-oriented subset of a data warehouse focusing on a particular business unit, department, subject area, or business functionality.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. Cloud-based DevOps provides a modern, agile environment for developing and maintaining applications and services that interact with the organization’s mainframe data. Best Practice 2. Best Practice 5.

Data Governance 67

Data Governance Database Cloud Data Data Lakes 67

Alation

MAY 16, 2023

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

Alation

FEBRUARY 13, 2020

Data curation is a term that has recently become a common part of data management vocabulary. Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. Curating data involves much more than storing data in a shared database.

Data Warehouse 52

Data Warehouse Data Lakes Data Governance Data Analyst 52

Tableau

MAY 11, 2022

At Tableau, we believe data is most valuable when everyone in an organization can use it to make better, data-driven decisions. At Tableau, we’re leading the industry with capabilities to connect to a wide variety of data, and we have made it a priority for the years to come. Here’s a look at what we provide today.

Tableau 95

Tableau Data Warehouse Database Data Analyst 95

AWS Machine Learning Blog

JUNE 5, 2023

One of the most common formats for storing large amounts of data is Apache Parquet due to its compact and highly efficient format. This means that business analysts who want to extract insights from the large volumes of data in their data warehouse must frequently use data stored in Parquet.

Machine Learning 71

Machine Learning Machine Learning AWS Data Lakes 71

Tableau

MAY 11, 2022

At Tableau, we believe data is most valuable when everyone in an organization can use it to make better, data-driven decisions. At Tableau, we’re leading the industry with capabilities to connect to a wide variety of data, and we have made it a priority for the years to come. Here’s a look at what we provide today.

Tableau 93

Tableau Data Warehouse Database Data Analyst 93

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 […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. What Is the Role of the Cloud in Data Modernization?

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

IBM Journey to AI blog

OCTOBER 12, 2023

Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc. To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture.

AI 77

AI AI Data Scientist Data Governance 77

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Alation

MAY 16, 2023

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

Data Pipeline 40

Data Pipeline Data Governance Data Lakes Data Warehouse 40

Alation

FEBRUARY 20, 2020

It’s no longer enough to build the data warehouse. Dave Wells, analyst with the Eckerson Group suggests that realizing the promise of the data warehouse requires a paradigm shift in the way we think about data along with a change in how we access and use it.

Data Warehouse 52

Data Warehouse Data Lakes Hadoop Data Preparation 52

Alation

JUNE 9, 2021

According to Gartner, data culture is a top priority for chief data officers (CDOs) and chief data & analytics officers (CDAOs). This post focuses on the role of data search & discovery within a data culture. The explosion in data and database types is a major pain point of the modern data consumer.

Data Governance 59

Data Governance Database Cloud Data Machine Learning 59

IBM Journey to AI blog

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. It enables secure data sharing for analytics and AI across your ecosystem.

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AWS Database AI AI 77

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Data Engineering 91

Data Engineering Data Engineer Data Engineering Data Engineering 91

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. This is especially helpful when handling massive amounts of big data.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Alation

APRIL 14, 2022

This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. The Cloud Data Migration Challenge. 8 Critical Analytics Tools for Cloud Environments.

Data Governance 59

Data Governance ML ML Cloud Data 59

Alation

NOVEMBER 2, 2022

It also helped that other analytics companies in Thoma Bravo’s portfolio echoed that positive feedback. We had not seen that in the broader intelligence & data governance market.”. Indeed, Alation’s accelerating growth mirrors the faster pace of data and analytics today. That was very unique.

Data Governance 98

Data Governance Data Lakes Data Warehouse Analytics 98

Alation

MARCH 1, 2022

Bill Hostmann, VP and Research Fellow at Dresner Advisory Services agrees “Data catalogs have emerged as a core set of capabilities for making content easier to find for analytic use cases, especially when there are multiple data sources being accessed for various analytic use cases. In 2022.1,

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

Tableau

FEBRUARY 14, 2022

The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse. Organizations that lack sound data management practices or that have struggled to build traction and confidence in their data and analytics deployment stand little chance of successfully embracing AI.

AI 74

AI AI Tableau Data Scientist 74

Tableau

FEBRUARY 14, 2022

The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse. Organizations that lack sound data management practices or that have struggled to build traction and confidence in their data and analytics deployment stand little chance of successfully embracing AI.

AI 72

AI AI Tableau Data Scientist 72