Data Quality Dimensions Are Crucial for AI

Dataversity

As organizations digitize customer journeys, the implications of low-quality data are multiplied manyfold. Since the data from such processes is growing, data controls may not be strong enough to ensure the data is qualitative.

How to Architect Data Quality on Snowflake

Dataversity

Without effective and comprehensive validation, a data warehouse becomes a data swamp. With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical.

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When It Comes to Data Quality, Businesses Get Out What They Put In

Dataversity

The post When It Comes to Data Quality, Businesses Get Out What They Put In appeared first on DATAVERSITY. Imagine you’ve invited your boss over for a dinner party to try to show off your culinary skills (and perhaps get a promotion).

What I Learned from Executing Data Quality Projects

The Data Administration Newsletter

Getting to great data quality need not be a blood sport! This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

How to Improve Data Quality by Using Feedback Loops

Dataversity

In this blog, we will take a look at: The impact poor Data Quality has on organizations and practical advice for how to overcome this challenge through the use of feedback loops. Poor Data Quality can cost organizations millions each year.

What to Expect in 2022: Data Privacy, Data Quality, and More

Dataversity

Three big shifts came this year, namely in the realms of consumer data privacy, the use of third-party cookies vs. first-party data, and the regulations and expectations […]. The post What to Expect in 2022: Data Privacy, Data Quality, and More appeared first on DATAVERSITY.

Why Synthetic Data Still Has a Data Quality Problem

Dataversity

According to Gartner, 85% of Data Science projects fail (and are predicted to do so through 2022). I suspect the failure rates are even higher, as more and more organizations today are trying to utilize the power of data to improve their services or create new revenue streams.

Data Quality Is In the Eye of the Beholder

The Data Administration Newsletter

1 In this article, I will apply it to the topic of data quality. I will do so by comparing two butterflies, each that represent a common use of data quality: firstly and most commonly in situ for existing systems, and secondly for use […].

Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance

Dataversity

Organizations are constantly coming to us wanting help in becoming more “data-driven.” The post Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance appeared first on DATAVERSITY. Click to learn more about author Terence Siganakis.

Data Quality Problems Everywhere You Look

The Data Administration Newsletter

Data is everywhere! But can you find the data you need? What can be done to ensure the quality of the data? How can you show the value of investing in data? Can you trust it when you get it?

Start Small and Scale Up with Data Profiling, Data Quality, and Data Governance

Dataversity

Organizations today are rallying business users around using data to make better business decisions. Business users want to know where that data lives, understand if people are accessing the right data at the right time, and be assured that the data is of high quality.

Data Management’s Next Frontier is Machine Learning-Based Data Quality

The Data Administration Newsletter

Regardless of how accurate a data system is, it yields poor results if the quality of data is bad. As part of their data strategy, a number of companies have begun to deploy machine learning solutions.

Good AI in 2021 Starts with Great Data Quality

Dataversity

The post Good AI in 2021 Starts with Great Data Quality appeared first on DATAVERSITY. Click here to learn more about Heine Krog Iversen. More and more companies want to use artificial intelligence (AI) in their organization to improve operations and performance.

Why Data Quality Matters

The Data Administration Newsletter

Quality is never an accident. ” John Ruskin, prominent Victorian era social thinker Data-driven decision-making is fast becoming a critical business strategy for organizations in every sector. It is always the result of intelligent effort.”

Data is Risky Business: Data Quality Discussion about Data Ethics

The Data Administration Newsletter

The Data Ethics Conundrum The recent DAMA EMEA conference was a valiant effort to connect the DAMA membership in the EMEA region through an innovative virtual conference format. One of these polls asked, “Are Data Ethics Principles Universal?”

Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC

Smart Data Collective

Companies that utilize data analytics to make the most of their business model will have an easier time succeeding with Amazon. One of the best ways to create a profitable business model with Amazon involves using data analytics to optimize your PPC marketing strategy.

What Is Data Quality?

Cprime

Data is often the most valuable asset for a company because it’s possible to use it in so many ways. You can use data to improve processes, gather insights, or predict trends through data analysis. What Is Data Quality? Why Does Data Quality Matter?

Expanding Role of Data Governance, Metadata Management, and Data Quality

The Data Administration Newsletter

Ensuring data quality is an important aspect of data management and these days, DBAs are increasingly being called upon to deal with the quality of the data in their database systems more than ever before. The importance of quality data cannot be overstated.

What is Data Quality - Definition, Dimensions, Characteristics, and How to Improve It | Simplilearn

Simplilearn

Data saturates the modern world. Data is information, information is knowledge, and knowledge is power, so data has become a form of contemporary currency, a valued commodity exchanged between participating parties.

Balance Data Quality with Data Agility!

ElegantJ BI

Data Quality vs. Data Agility – A Balanced Approach! When it comes to analytical quality versus analytical agility, we might see the issue in the same light. Original Post: Data Quality and Data Agility are Both Important to Success!

The Importance of Data Quality in Financial Reporting

Insight Software

Data quality has always been at the heart of financial reporting , but with rampant growth in data volumes, more complex reporting requirements and increasingly diverse data sources, there is a palpable sense that some data, may be eluding everyday data governance and control.

Data Quality Management: Growing Role in Big Data Initiatives [Updated] | Simplilearn

Simplilearn

Data is at the heart of everything important for businesses these days. Whether it’s customer data, sales forecasts, supply chain scheduling, or any other critical process, data drives most business operations.

Data Agility and Popularity vs Data Quality in Self-Serve BI and Analytics!

ElegantJ BI

One of the most valuable aspects of self-serve business intelligence is the opportunity it provides for data and analytical sharing among business users within the organization. So, there is definitely a need to provide both approaches in data analysis.

Data Agility and ‘Popularity’? vs. Data Quality in Self-Serve BI and Analytics!

ElegantJ BI

One of the most valuable aspects of self-serve business intelligence is the opportunity it provides for data and analytical sharing among business users within the organization. So, there is definitely a need to provide both approaches in data analysis.

How to Take Advantage of Data Commerce Platforms

Dataversity

In today’s digital world, data has become critical to the success of companies across all industries. The highest-performing organizations utilize data to make better business decisions, generate new revenue streams, and grow faster than their competitors.

Governors of Data: A Song About Data Governance

Dataversity

Editor’s Note: Data professional Tiankai Feng writes and performs songs about everything from lockdown to virtual meetings to analytics. We here at DATAVERSITY can’t stop humming “Governors of Data,” his catchy and clever ode to Data Governance – and we think you’ll enjoy it too.

Data Projects Should Start with Data Governance

Dataversity

The hallmark of any successful Data Governance implementation is awareness. The post Data Projects Should Start with Data Governance appeared first on DATAVERSITY.

6 Data Cleaning Strategies Your Company Needs Right Now

Dataversity

Data cleaning (or data cleansing) is the process of checking your data for correctness, validity, and consistency and fixing it when necessary. No matter what type of data you are handling, its quality is crucial. What are the specifics of data […].

Is DataOps the Savior of Under-Pressure Analytics Teams?

Dataversity

DataOps is something that has been building up at the edges of enterprise data strategies for a couple of years now, steadily gaining followers and creeping up the agenda of data professionals. The number of data requests from the business keeps growing […].

5 Common Data Governance Challenges (and How to Overcome Them)

Dataversity

It’s common for enterprises to run into challenges such as lack of data visibility, problems with data security, and low Data Quality. The post 5 Common Data Governance Challenges (and How to Overcome Them) appeared first on DATAVERSITY.

Solving Three Data Problems with Data Observability

Dataversity

Data collection, while crucial to the overall functionality and health of a business, does not automatically lead to success. If data processes are not at peak performance and efficiency, businesses are just collecting massive stores of data for no reason.

The Power of “Set It and Forget It” Data Governance

Dataversity

In addition, the volume and variety of information and content grows exponentially by the day, making effective Data Governance a tough task for many companies. The post The Power of “Set It and Forget It” Data Governance appeared first on DATAVERSITY.

16 Internal Data Management Best Practices

Dataversity

In today’s digital world, data is undoubtedly a valuable resource that has the power to transform businesses and industries. As the saying goes, “data is the new oil.” However, in order for data to be truly useful, it needs to be managed effectively.

How to Build Data Governance Programs That Last: A Business-First Approach

Dataversity

Data analytics and AI play an increasingly pivotal role in most modern organizations. To keep those initiatives on track, enterprises must roll out Data Governance programs to ensure data integrity, compliance, and optimal business value.

New in Tableau Catalog: Improved search and monitoring for data quality warnings

Tableau

Data discovery and trust have been core principles of Tableau Catalog (part of Tableau Data Management ) since its introduction with Tableau 2019.3. With every release, we continue to add features that help users find and use trusted data with confidence. Kate Grinevskaja.