Astera

APRIL 7, 2023

Currently, around 30% of the world’s data is produced by the healthcare industry and this percentage is expected to reach 35% by 2025. The sheer amount of health-related data presents countless opportunities. 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

NOVEMBER 13, 2023

But have you ever wondered how data informs the decision-making process? The key to leveraging data lies in how well it is organized and how reliable it is, something that an Enterprise Data Warehouse (EDW) can help with. What is an Enterprise Data Warehouse (EDW)?

Data Warehouse 52

Data Warehouse E-Commerce Supply Chain Real-time Data 52

Astera

APRIL 13, 2023

In the digital age, a data warehouse plays a crucial role in businesses across several industries. It provides a systematic way to collect and analyze large amounts of data from multiple sources, such as marketing, sales, finance databases, and web analytics. What is a Data Warehouse?

Data Warehouse 52

Data Warehouse Data Mining Business Intelligence Business Intelligence 52

Astera

NOVEMBER 13, 2023

D ata is the lifeblood of informed decision-making, and a modern data warehouse is its beating heart, where insights are born. In this blog, we will discuss everything about a modern data warehouse including why you should invest in one and how you can migrate your traditional infrastructure to a modern data warehouse.

Data Warehouse 52

Data Warehouse Real-time Data Planning Agile 52

Astera

APRIL 23, 2024

To do so, they need data quality metrics relevant to their specific needs. Organizations use data quality metrics, also called data quality measurement metrics, to assess the different aspects, or dimensions, of data quality within a data system and measure the data quality against predefined standards and requirements.

Data Quality 52

Data Quality Monitoring Data Modelling Data Warehouse 52

Astera

JANUARY 1, 2024

What Is Data Quality? Data quality is the measure of data health across several dimensions, such as accuracy, completeness, consistency, reliability, etc. In short, the quality of your data directly impacts the effectiveness of your decisions.

Data Quality 52

Data Quality Data Governance Government Data Warehouse 52

Astera

JANUARY 1, 2024

What Is Data Quality? Data quality is the measure of data health across several dimensions, such as accuracy, completeness, consistency, reliability, etc. In short, the quality of your data directly impacts the effectiveness of your decisions.

Data Quality 52

Data Quality Data Governance Government Data Warehouse 52

Insight Software

JANUARY 20, 2021

As the volume of available information continues to grow, data management will become an increasingly important factor in effective business management. Lack of proactive data management, on the other hand, can result in incompatible or inconsistent sources of information, as well as data quality problems.

Data Management 95

Data Management Data Analytics Data Analytics E-Commerce 95

Domo

MAY 27, 2021

1 – There were significant quantified benefits over a 3-year period A composite organization, representative of the four interviewees’ organizations, experienced a three-year present value increase of more than $1 million in revenue as well as over $1 million in labor savings. That’s entirely eliminated.” million and an ROI of 345%.

Data Warehouse 93

Data Warehouse Financial Analysis Data Quality 93

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 130

Big Data Data Analytics Data Analytics Data Management 130

Dataversity

NOVEMBER 1, 2021

Many in enterprise Data Management know the challenges that rapid business growth can present. Whether through acquisition or organic growth, the amount of enterprise data coming into the organization can feel exponential as the business hires more people, opens new locations, and serves new customers.

Data Governance 130

Data Governance Government Data Management Master Data Management 130

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

Data Pine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

AUGUST 29, 2024

It enables easy data sharing and collaboration across teams, improving productivity and reducing operational costs. Identifying Issues Effective data integration manages risks associated with M&A. Step 2: Data Mapping and Profiling This step involves understanding the relationships between data elements from different systems.

Data Governance 52

Data Governance Data Warehouse Data Quality Government 52

Data Pine

OCTOBER 25, 2022

That said, we’ve selected 16 of the world’s best business intelligence books – invaluable resources that have not only earned a great deal of critical acclaim but are what we consider to be wonderfully presented, incredibly informational, and decidedly digestible. One of the best books on building a BI system, hands down.

Business Intelligence 117

Business Intelligence Business Intelligence Big Data Data Mining 117

The BAWorld

SEPTEMBER 18, 2024

Properly executed, data integration cuts IT costs and frees up resources, improves data quality, and ignites innovation—all without systems or data architectures needing massive rework. How does data integration work? Extract: Data is pulled from its source.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Astera

JUNE 6, 2023

As the volume and complexity of data continue to rise, effective management and processing become essential. The best data pipeline tools offer the necessary infrastructure to automate data workflows, ensuring impeccable data quality, reliability, and timely availability.

Data Warehouse 52

Data Warehouse Monitoring Real-time Data Documentation 52

Astera

DECEMBER 16, 2022

Businesses operating in the tech industry are among the most significant data recipients. The rise of big data has sharply raised the volume of data that needs to be gathered, processed, and analyzed. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. See Case Sudy.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

Astera

DECEMBER 16, 2022

Businesses operating in the tech industry are among the most significant data recipients. The rise of big data has sharply raised the volume of data that needs to be gathered, processed, and analyzed. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. See Case Sudy.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

Astera

DECEMBER 2, 2022

Businesses operating in the tech industry are among the most significant data recipients. The rise of big data has sharply raised the volume of data that needs to be gathered, processed, and analyzed. These large data volumes present numerous challenges for companies, especially those with outdated data management systems.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

Astera

DECEMBER 18, 2023

For instance, if the extracted data contains missing values or outliers, these issues are addressed during the transformation process to ensure data accuracy. Finally, the transformed data is loaded into a target system or data warehouse for reporting and analysis. How CDC Works in Data Integration?

Finance 52

Finance Banking Real-time Data Data Warehouse 52

Astera

MAY 25, 2023

That’s how it can feel when trying to grapple with the complexity of managing data on the cloud-native Snowflake platform. They range from managing data quality and ensuring data security to managing costs, improving performance, and ensuring the platform can meet future needs.

Data Quality 52

Data Quality Government Data Governance Monitoring 52

Actian

DECEMBER 9, 2018

This is important for leaders to understand, because it means the information they use for decision-making, unless it is real-time data, doesn’t likely reflect the current reality. If they don’t have accurate information about how things are presently, then how can they be expected to make informed decisions about the future?

Data Warehouse 40

Data Warehouse Real-time Data Agile Data Quality 40

Astera

MAY 31, 2024

Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. While both fields help you extract insights from data, data analytics focuses more on analyzing historical data to guide decisions in the present. Data warehouses and data lakes play a key role here.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

DECEMBER 22, 2022

Challenge # 1: Inability to Process Growing Data Volumes. The volume of global data is projected to rise to 175 Zettabytes by 2025. This presents the challenge of accurately capturing this data in a timely manner. Enterprises need to capture and store unstructured data to extract valuable insights.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

Astera

SEPTEMBER 4, 2024

Choose and Implement The Right Data Strategy with Astera Leverage our data expertise to figure out the best data architecture for your organization. Discuss your data strategy with us. What Is Data Mesh? Data mesh was first presented as a concept by Zhamak Dehghani in 2019. What is Data Fabric?

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

Ntara

JUNE 23, 2021

Businesses waste tens of thousands of hours per year tracking down the “right” version of their product data and putting it into the “right” format, often duplicating time and effort. Disorganized product data presents the same challenges and inefficiencies. Any data repository can be a potential inbound source.

Documentation 52

Documentation Data Quality Data Warehouse Data Management 52

Business Analysis Knowledge Share

OCTOBER 27, 2023

Enhanced Data Governance : Use Case Analysis promotes data governance by highlighting the importance of data quality , accuracy, and security in the context of specific use cases. The data collected should be integrated into a centralized repository, often referred to as a data warehouse or data lake.

Business Intelligence 52

Business Intelligence Business Intelligence Supply Chain Data Governance 52

Astera

DECEMBER 18, 2023

For instance, if the extracted data contains missing values or outliers, these issues are addressed during the transformation process to ensure data accuracy. Finally, the transformed data is loaded into a target system or data warehouse for reporting and analysis. How CDC Works in Data Integration?

Finance 40

Finance Banking Real-time Data Data Warehouse 40

Astera

OCTOBER 31, 2023

Data preparation (also known as data prep ) is the process of standardizing data into the desired output. By converting unstructured data into a structured format, data preparation enables comprehensive data analysis that can reveal hidden insights and opportunities.

Data Quality 52

Data Quality Documentation Data Warehouse Data Governance 52

Astera

MAY 13, 2024

It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. 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

AUGUST 16, 2024

Let’s look at some reasons data migration projects fail: Risk of Data Integrity Loss Data quality maintenance is crucial to a smooth data migration process, especially when dealing with large volumes of data. Improper planning can lead to data corruption or loss.

Digital Transformation 52

Digital Transformation Planning Government Cloud Computing 52

MindsMapped

JULY 18, 2020

Business Analysts and Business Analytics – Differences.

Business Analysis 46

Business Analysis Business Analysis Requirements Gathering Documentation 46

Astera

AUGUST 22, 2023

Reusable Artifacts: Astera’s data preparation scripts are reusable across various artifacts (dataflow, workflow, analytics workbench), promoting efficient and consistent data processing throughout multiple workflows. It offers an instant preview and feedback on data quality, helping you ensure the accuracy and integrity of your data.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Astera

MAY 30, 2024

Statistical Analysis : Using statistics to interpret data and identify trends. Predictive Analytics : Employing models to forecast future trends based on historical data. Data Visualization : Presenting data visually to make the analysis understandable to stakeholders.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

The BAWorld

NOVEMBER 22, 2021

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98