BizAcuity

JANUARY 31, 2023

Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture. Data governance and security measures are critical components of data strategy.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Mining 130

Domo

MAY 30, 2024

By establishing a strong foundation, improving your data integrity and security, and fostering a data-quality culture, you can make sure your data is as ready for AI as you are. At first, your data set may have some of the right rows, some of the wrong ones, and some missing entirely.

Data Quality 105

Data Quality Data Governance Government Data Security 105

Astera

MAY 25, 2023

Big Data Security: Protecting Your Valuable Assets In today’s digital age, we generate an unprecedented amount of data every day through our interactions with various technologies. The sheer volume, velocity, and variety of big data make it difficult to manage and extract meaningful insights from.

Big Data 40

Big Data Data Security Monitoring Data Quality 40

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. How are your devices physically secured?

Data Quality 101

Data Quality Data Security Data Architecture Agile 101

Astera

DECEMBER 16, 2024

Pricing Model Issues: Several users have also complained that the solution is too expensive for big data syncs, while others consider it unpredictable because the pricing is dependent on the volume of data (i.e., Similarly, the custom plans are also not very customizable. Integrate.io

Data Warehouse 52

Data Warehouse Real-time Data Monitoring Data Quality 52

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Large volumes of data, organizations that require good data governance and integration of data sources, use by IT, MIS, data scientists and business analysts. Advantages: Can handle governance and data quality of a great deal of data coming from various types of data sources.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Large volumes of data, organizations that require good data governance and integration of data sources, use by IT, MIS, data scientists and business analysts. Advantages: Can handle governance and data quality of a great deal of data coming from various types of data sources.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Large volumes of data, organizations that require good data governance and integration of data sources, use by IT, MIS, data scientists and business analysts. Advantages: Can handle governance and data quality of a great deal of data coming from various types of data sources.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

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

MAY 22, 2024

It ensures consistent data policies and rules are applied, creating data reliability. Building a solid data governance framework involves several key pillars. Data Managers: Data managers oversee the technical infrastructure that stores and manages data assets.

Data Governance 52

Data Governance Government Data Discovery Data Security 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

Astera

APRIL 29, 2024

This strategic approach to data governance aligns with findings from a McKinsey survey , suggesting that companies with solid data governance strategies are twice as likely to prioritize important data — leading to better decision-making and organizational success. What is a Data Governance Strategy?

Data Governance 52

Data Governance Government IBM Maintenance Data Quality 52

Astera

MARCH 20, 2024

Enterprise data management (EDM) is a holistic approach to inventorying, handling, and governing your organization’s data across its entire lifecycle to drive decision-making and achieve business goals. It provides a strategic framework to manage enterprise data with the highest standards of data quality , security, and accessibility.

Data Management 52

Data Management Master Data Management Government Data Warehouse 52

Astera

APRIL 10, 2023

By following these five best practices businesses can successfully integrate their data, improve efficiency, and gain valuable insights into their operations. Ensure Data Quality Management One of the most critical aspects of big data integration is ensuring that the data being integrated is of high quality.

Big Data 52

Big Data IBM Maintenance IBM cost Data Quality 52

Business Analysis Knowledge Share

OCTOBER 27, 2023

The Significance of Business Intelligence Business Intelligence is a multifaceted discipline that encompasses the tools, technologies, and processes for collecting, storing, and analyzing data to support informed decision-making. Data integration ensures that all necessary information is readily available for analysis.

Business Intelligence 52

Business Intelligence Business Intelligence Supply Chain Data Governance 52

Astera

MARCH 19, 2024

It involves developing and enforcing policies, procedures, and standards to ensure data is consistently available, accurate, secure, and compliant throughout its lifecycle. At its core, data governance aims to answer questions such as: Who owns the data? What data is being collected and stored? Is the data secure?

Data Governance 52

Data Governance Government Data Quality Monitoring 52

Astera

FEBRUARY 28, 2024

Best Practices for Data Warehouses Adopting data warehousing best practices tailored to your specific business requirements should be a key component of your overall data warehouse strategy. Performance Optimization Boosting the speed and efficiency of data warehouse operations is the key to unleashing its full potential.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

AUGUST 30, 2024

Your organization will need to strategize and plan carefully to execute it. Plus, you’ll need a specialized cloud migration solution to ensure your data’s security, integrity, and availability. To resolve this, back up your data and have a recovery plan.

Data Governance 52

Data Governance Government Data Quality Documentation 52

Domo

OCTOBER 24, 2024

The analyst firm cites that organizations of all sizes pay the most attention to BI priorities associated with data security, data quality, reporting, dashboards and data visualization, and indicates that small organizations are relatively more influenced by executive management, operations, IT, customer service or sales.

Business Intelligence 52

Business Intelligence Business Intelligence Cloud Computing Customer Experience 52

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

MAY 20, 2024

Data provenance answers questions like: What is the source of this data? Who created this data? This information helps ensure data quality, transparency, and accountability. This proactive approach enhances the overall trust in the data and streamlines data validation processes.

Data Governance 52

Data Governance Healthcare Government Data Quality 52

Domo

AUGUST 2, 2023

The report includes in-depth analyses of BI topics such as adoption and deployment, data leadership, organization budgets, data literacy and objectives and achievements. This year’s report found that out of 59 topics, data security, data quality and reporting are the top technologies and initiatives strategic to BI.

Business Intelligence 52

Business Intelligence Business Intelligence Cloud Computing Customer Experience 52

Astera

FEBRUARY 27, 2024

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

Data Warehouse 52

Data Warehouse Data Quality Cloud Computing Monitoring 52

Astera

FEBRUARY 27, 2024

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

Data Warehouse 52

Data Warehouse Data Quality Cloud Computing Monitoring 52

Astera

DECEMBER 16, 2022

Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Challenge#1: Accessing organizational data. A significant aspect of a well-planned data management strategy involves knowing your organization’s data sources and where the business data resides.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

Astera

DECEMBER 16, 2022

Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Challenge#1: Accessing organizational data. A significant aspect of a well-planned data management strategy involves knowing your organization’s data sources and where the business data resides.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

Astera

DECEMBER 2, 2022

Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Challenge#1: Accessing organizational data. A significant aspect of a well-planned data management strategy involves knowing your organization’s data sources and where the business data resides.

Data Management 52

Data Management Data Warehouse Big Data Procurement 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

MAY 23, 2023

It involves gathering, storing, and analyzing sports data to gain insights into the performance of players and teams and making predictions for upcoming games. Discovering patterns in the data unlocks potential for powerful uses such as creating customized training plans for athletes.

Data Analytics 40

Data Analytics Data Analytics Data Security Predictive Analytics 40

Astera

MAY 13, 2024

Data Aggregation Types and Techniques There are various types of data aggregation. Your requirements and how you plan to use the data will determine which approach suits your use case. Temporal As the name suggests, temporal aggregation summarizes data over specified time intervals.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

JULY 3, 2024

Data architecture is important because designing a structured framework helps avoid data silos and inefficiencies, enabling smooth data flow across various systems and departments. An effective data architecture supports modern tools and platforms, from database management systems to business intelligence and AI applications.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Astera

SEPTEMBER 20, 2023

Data Movement Data movement from source to destination, with minimal transformation. Data movement involves data transformation, cleansing, formatting, and standardization. Data Quality Consideration Emphasis is on data availability rather than extensive data quality checks.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

Data Movement Data movement from source to destination, with minimal transformation. Data movement involves data transformation, cleansing, formatting, and standardization. Data Quality Consideration Emphasis is on data availability rather than extensive data quality checks.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

DECEMBER 22, 2022

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. But without proper storage planning and solution, this increasing data volumes put pressure on existing storage capacity. Download Your Free Ebook.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

Astera

MAY 9, 2023

To mitigate business risks that are associated with storing data that is sensitive. Businesses must have an effective strategy for data governance to ensure meeting regulatory compliances, minimizing risks, improving data security, and creating accountability for their data.

Data Governance 40

Data Governance Government Data Management Data Security 40

Data Pine

MAY 31, 2022

It provides better data storage, data security, flexibility, improved organizational visibility, smoother processes, extra data intelligence, increased collaboration between employees, and changes the workflow of small businesses and large enterprises to help them make better decisions while decreasing costs.

Cloud Computing 95

Cloud Computing Cybersecurity Business Intelligence Business Intelligence 95

Astera

AUGUST 16, 2024

McKinsey reports that inefficiencies in data migration cost enterprises 14% more than their planned spending. 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.

Digital Transformation 52

Digital Transformation Planning Government Cloud Computing 52