Dataversity

DECEMBER 7, 2020

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

Data Warehouse 90

Data Warehouse Business Intelligence Business Intelligence Analytics 90

Data Science Dojo

SEPTEMBER 6, 2023

M aintaining the security and governance of data within a data warehouse is of utmost importance. Data Security: A Multi-layered Approach In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information.

Data Warehouse 195

Data Warehouse Data Governance Data Quality ETL 195

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Alation

JULY 28, 2022

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. The cloud is no longer synonymous with risk. What do you migrate, how, and when?

Data Warehouse 69

Data Warehouse Cloud Data Data Governance Database 69

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Big Data 59

Dataconomy

SEPTEMBER 27, 2024

The global data analytics market is forecasted to increase by USD 234.4 To learn more about the trends of data analytics fields, their prospects, and their challenges, we talked to Aksinia Chumachenko, Product Analytics Team Lead at Simpals, Moldova’s leading digital company. billion from 2023 to 2028.

Analytics 113

Analytics Analytics Big Data Big Data 113

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.

Data Lakes 59

Data Lakes Data Warehouse Data Quality Data Governance 59

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. Both approaches aim to improve data quality and enable accurate analysis.

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ETL Data Quality Data Warehouse Analytics 105

Dataversity

FEBRUARY 1, 2021

Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […]. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3 appeared first on DATAVERSITY.

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

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.

Data Governance 111

Data Governance Data Warehouse Cloud Data Analytics 111

Dataversity

JANUARY 11, 2021

Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […]. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 2 appeared first on DATAVERSITY.

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Tableau

APRIL 18, 2022

Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. . At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. . At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 98

Tableau Data Quality Analytics Analytics 98

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Reference data management.

Data Warehouse 98

Data Warehouse SQL Azure ETL 98

Tableau

SEPTEMBER 13, 2021

release enhances Tableau Data Management features to provide a trusted environment to prepare, analyze, engage, interact, and collaborate with data. Automate your Prep flows in a defined sequence, with automatic data quality warnings for any failed runs. Enable data quality warnings for email subscriptions to dashboards.

Tableau 102

Tableau Data Quality Data Preparation Data Warehouse 102

Smart Data Collective

OCTOBER 13, 2021

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

Data Visualization 145

Data Visualization Big Data Big Data Predictive Analytics 145

Tableau

SEPTEMBER 13, 2021

release enhances Tableau Data Management features to provide a trusted environment to prepare, analyze, engage, interact, and collaborate with data. Automate your Prep flows in a defined sequence, with automatic data quality warnings for any failed runs. Enable data quality warnings for email subscriptions to dashboards.

Tableau 98

Tableau Data Quality Data Preparation Data Warehouse 98

IBM Journey to AI blog

OCTOBER 22, 2024

Indeed, IDC has predicted that by the end of 2024, 65% of CIOs will face pressure to adopt digital tech , such as generative AI and deep analytics. The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Precisely

OCTOBER 23, 2023

As more organizations tap into the value of advanced analytics and AI, MDM has emerged as a vital element for trusted data and confident decisions. An ERP does not do data quality very well. CRM’s, likewise, does a poor job of undating data according to consistent standards. MDM is real-time.

Data Quality 110

Data Quality Data Warehouse Analytics Analytics 110

AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. You can review the recommendations and augment rules from over 25 included data quality rules.

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AWS ML ML Data Quality 84

Dataversity

FEBRUARY 13, 2024

Are you drowning in data? Feeling shackled by rigid data warehouses that can’t keep pace with your ever-evolving business needs? Traditional data storage strategies are crumbling under the weight of diverse data sources, leaving you with limited analytics and frustrated decisions. You’re not alone.

Data Warehouse 59

Data Warehouse Analytics Analytics Data Governance 59

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. This step is vital for maintaining data integrity and quality.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

phData

APRIL 10, 2023

In almost every modern organization, data and its respective analytics tools serve to be that big blue crayon. Users across the organization need that big blue crayon to make decisions every day, answer questions about the business, or drive changes based on data. What is Governed Self-Service Analytics? Let’s dive in.

Analytics 52

Analytics Analytics Data Governance Data Modeling 52

Pickl AI

NOVEMBER 4, 2024

Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

Pickl AI

JULY 23, 2023

Summary: In the modern digital landscape, data analytics has emerged as a powerful tool for businesses and industries seeking valuable insights to drive decision-making and improve performance. Today, it is imperative for companies to adopt the data driven decision making processes.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Database 130

Database Data Visualization Big Data Big Data 130

IBM Journey to AI blog

JULY 3, 2024

Creating a trusted data foundation is enabling high quality, reliable, secure and governed data and metadata management so that it can be delivered for analytics and AI applications while meeting data privacy and regulatory compliance needs.

AI 45

AI AI Data Quality Database 45

phData

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Dimensional modelling has emerged as a powerful methodology for structuring data in a way that enhances the efficiency of querying and reporting.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52