Data Strategy
Quality data is crucial for automation, pattern recognition, and training AI for advanced capabilities. A data-first mindset and a data-focused platform are essential for long-term success
oracle.com • Generative AI Changes Everything for the CFO and Finance
The amount of data we now access has grown far faster than the general level of data literacy in companies. Most companies have too much data, it’s stored in too many places, it’s not ‘clean’ and it’s often more confusing than helpful when it comes to what matters – making decisions with it. We need to ensure companies create centralized yet
... See moreTom Goodwin • Digital Darwinism: Survival of the Fittest in the Age of Business Disruption (Kogan Page Inspire)
In today’s data world, there are so many options for an EL tool to avoid you developing your own extracting script and to help you gain a LOT of time.
Fivetran, Mage, and Airbyte to mention a few.
You don’t have to maintain custom scripts, these tools come with +300 connectors, basic scheduling, and error handling.
Jeremy • What I Learned After One Year of Building a Data Platform From Scratch
Data quality management ensures data is fit for consumption and meets the needs of data consumers. To be of high quality, data must be consistent and unambiguous. You can measure data quality through dimensions including accuracy, completeness, consistency, integrity, reasonability, timelines, uniqueness, validity, and accessibility.
Astasia Myers • 4 Data Trends to Watch in 2020
How_to_Enable_Self-S_748717_ndx
The research outlines best practices for enabling self-service analytics, emphasizing alignment with business goals, collaborative development between IT and business, and lightweight management for effective data and analytics success.
LinkHow to Enable Self-Service Analytics to Ensure D&A Success
The purpose of metadata is not simply to describe data and information assets, but rather to proactively answer questions that consumers might have about them. Where did this data come from? How up to date is it? How trustworthy is it? What business process(es) created it? What business process(es) use it? What transformations or filtering have... See more
Larry Burns • The Currency of Information: Managing Data as an Asset (Part Three)
One of the problems with owning your own data is that it ignores the question of what format that data is in. Data formats are sometimes considered carefully, but they can also be hammered out fast to get a minimum viable product out the door.
Byrne Hobart • The Promise and Paradox of Decentralization
This brings us to our third point: Because data only has meaning within a particular context, consumers of data and information need metadata to help them decide how to use it. This is an important difference between data and other assets. You don’t need much metadata when deciding whether to spend a $20 bill, but you do need metadata when trying... See more