ElegantJ BI

SEPTEMBER 1, 2021

With a targeted self-serve data preparation tool, the midsized business can allow its business users to take on these tasks without the need for SQL skills, ETL or other programming language or data scientist skills.

Data Quality 130

Data Quality Visualization Data Modelling Agile 130

Dataversity

JUNE 19, 2023

In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline.

Monitoring 130

Monitoring Data Modelling Data Quality Data Governance 130

Sisense

APRIL 15, 2021

Your company is gathering data (and has likely been doing so for years), and you’ve probably got a system or two to glean insights from that data to make smarter decisions. Team members with data skills including SQL, Python, R, and other prototyping methodologies can work directly to enhance analytics modeling platforms like Sisense.

Artificial Intelligence 98

Artificial Intelligence Data Modelling Cloud Computing Data Discovery 98

Dataversity

MAY 1, 2023

Many organizations have mapped out the systems and applications of their data landscape. Many have modeled their data domains and key attributes. The remainder of this point of view will explain why connecting […] The post Connecting the Three Spheres of Data Management to Unlock Value appeared first on DATAVERSITY.

Data Management 244

Data Management Documentation Data Modelling Data Quality 244

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

Sisense

JANUARY 14, 2021

Especially when dealing with business data, trust in the figures is an essential element of every transaction. VP of Business Intelligence Michael Hartmann describes the problem: “When an upstream data model change was introduced, it took a few days for us to notice that one of our Sisense charts was ‘broken.’

E-Commerce 85

E-Commerce Business Intelligence Business Intelligence Data Modelling 85

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.

Planning 246

Planning Data Warehouse Data Modelling Data Quality 246

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Dataversity

MAY 3, 2024

Commerce today runs on data – guiding product development, improving operational efficiency, and personalizing the customer experience. However, many organizations fall into the trap of thinking that more data means more sales, when these two factors aren’t directly correlated.

Digital Transformation 189

Digital Transformation Customer Experience Customer Experience Digital 189

Astera

MARCH 7, 2024

These tests validate and verify the data to ensure accuracy and minimize data loss. This blog offers an in-depth discussion on ETL testing and its types, its necessity, the steps it entails, and how to do it right. Data now heavily impacts businesses at all levels, from everyday operations to strategic decisions.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Modelling 52

Astera

FEBRUARY 28, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 14, 2024

Data vault is an emerging technology that enables transparent, agile, and flexible data architectures, making data-driven organizations always ready for evolving business needs. What is a Data Vault?  A data vault is a data modeling technique that enables you to build data warehouses for enterprise-scale analytics.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Astera

JUNE 12, 2024

Data Governance establishes framework, policies, and processes for managing data assets within an organization. Focus Flow of data Origin and history of data Management and control of data assets Purpose Ensure data quality, traceability, and compliance. How was the data created?

Data Governance 52

Data Governance Government Data Quality Monitoring 52

Astera

APRIL 7, 2023

A robust data warehouse architecture does everything in data management—including ETL (extraction, transformation, loading)—while ensuring data quality, consistency, speedy retrieval, and enhanced security at all times. Improving Data Quality and Consistency Quality is essential in the realm of data management.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

AUGUST 30, 2024

In this blog, you will learn about on-premise to cloud migration, its different types, challenges, and best practices. An on-premise to cloud migration entails moving infrastructure and data from an on-premise system (third-party data centers or infrastructure housed locally) to the cloud (public, private, or hybrid).

Data Governance 52

Data Governance Government Data Quality Documentation 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

APRIL 28, 2023

By AI taking care of low-level tasks, data engineers can focus on higher-level tasks such as designing data models and creating data visualizations. For instance, Coca-Cola uses AI-powered ETL tools to automate data integration tasks across its global supply chain to optimize procurement and sourcing processes.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

FEBRUARY 16, 2024

It facilitates the seamless collection, consolidation, and transformation of data from diverse sources and systems into a unified and standardized format. The advantages of this integration extend beyond mere organization; it significantly improves data quality and accuracy.

Finance 52

Finance Banking Data Quality Artificial Intelligence 52

Astera

JULY 3, 2024

It organizes data for efficient querying and supports large-scale analytics. Data warehouse architecture defines the structure and design of a centralized repository for storing and analyzing data from various sources. Each type of data architecture—centralized or distributed—has unique strengths and use cases.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Astera

JANUARY 2, 2024

Securing Data: Protecting data from unauthorized access or loss is a critical aspect of data management which involves implementing security measures such as encryption, access controls, and regular audits. Organizations must also establish policies and procedures to ensure data quality and compliance.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Astera

NOVEMBER 1, 2023

Data Integration: A data warehouse enables seamless integration of data from various systems and eliminates data silos and promotes interoperability and overall performance. Data-driven Finance with Astera Download Now Who Can Benefit from a Finance Data Warehouse?

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

Astera

MAY 13, 2024

This blog offers an in-depth look at data aggregation to help you understand what it is, how it works, and how it benefits your business when done right. Understanding Data Aggregation What is Data Aggregation? Besides being relevant, your data must be complete, up-to-date, and accurate.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

JANUARY 23, 2024

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

Agile 52

Agile Data Warehouse Data Quality Government 52

Dataversity

FEBRUARY 19, 2021

Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel. Click to learn more about author Tejasvi Addagada.

Business Intelligence 147

Business Intelligence Business Intelligence Data Modelling Data Discovery 147

Astera

AUGUST 13, 2024

Data-first modernization is a strategic approach to transforming an organization’s data management and utilization. It involves making data the center and organizing principle of the business by centralizing data management, prioritizing data quality , and integrating data into all business processes.

Data Governance 52

Data Governance Data Architecture Data Quality Real-time Data 52

Astera

JANUARY 24, 2024

Key Features of Astera It offers customized data quality rules so you can get to your required data faster and remove irrelevant entries more easily. It provides multiple security measures for data protection. Features built-in data quality tools, such as the Data Quality Firewall, and error detection.

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Astera

MARCH 28, 2024

Additionally, data catalogs include features such as data lineage tracking and governance capabilities to ensure data quality and compliance. On the other hand, a data dictionary typically provides technical metadata and is commonly used as a reference for data modeling and database design.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Business Analysts

APRIL 5, 2023

Data analysis and modelling : AI projects require large amounts of data to train machine learning models. Business analysts can help organizations identify the data sources needed for AI projects, perform data analysis, and develop data models.

Artificial Intelligence 52

Artificial Intelligence Business Analysis Business Analysis Requirements Gathering 52

Astera

JANUARY 18, 2024

Fivetran is also not an ideal solution if you are looking for a complete enterprise-grade data management solution as it doesn’t support data governance or offer advanced capabilities to improve data quality. All you need to do is just drag and drop the transformations in the data flow designer.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

DECEMBER 22, 2022

It’s one of the three core data types, along with structured and semi-structured formats. Examples of unstructured data include call logs, chat transcripts, contracts, and sensor data, as these datasets are not arranged according to a preset data model. This makes managing unstructured data difficult.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

Astera

JULY 13, 2023

MDM ensures data consistency, reduces duplication, and enhances data quality across systems. It is particularly useful in scenarios where data integrity, data governance, and data quality are of utmost importance, such as customer data management, product information management, and regulatory compliance.

Data Warehouse 40

Data Warehouse Data Quality Data Governance Master Data Management 40

Dataversity

FEBRUARY 17, 2021

Click to learn more about author Steve Zagoudis. Successful problem solving requires finding the right solution to the right problem. We fail more often because we solve the wrong problem than because we get the wrong solution to the right problem.” – Russell L.

Data Warehouse 130

Data Warehouse Data Modelling Data Governance Data Quality 130

Dataversity

JULY 12, 2021

In my eight years as a Gartner analyst covering Master Data Management (MDM) and two years advising clients and prospects at a leading vendor, I have seen first-hand the importance of taking a multidomain approach to MDM. Click to learn more about author Bill O’Kane.

Master Data Management 130

Master Data Management Data Management Data Quality Data Governance 130

The BAWorld

SEPTEMBER 6, 2024

It has mainly focused on identifying the data errors, inconsistencies and inaccuracies in the data and make sure that is accurate, complete and reliable for data analytics. Why is data cleaning important? As mentioned above there are many uses of data. This issue can affect data analysis practices.

Data Analytics 40

Data Analytics Data Analytics Data Quality Data Modelling 40

Astera

SEPTEMBER 1, 2023

Data Integration: A data warehouse supports data integration across various subsidiaries, systems, and data formats, fostering interoperability and reducing data silos. Fraud Detection & Prevention Using Data Warehouse Utilizing a data warehouse, insurance companies can improve their fraud detection process.

Data Warehouse 40

Data Warehouse Data Modelling Data Quality Data Security 40