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Delivering New Business Success Requires a Unified Data Space

by; Mark Stadtmueller, VP Product Strategy, Lucd

analysis of data

Nothing in business is passive. Every day that a business operates is driven by a strategy. Even having no strategy is a strategy. Whatever that strategy is, it drives growth. No matter if it is a food truck business deciding on food type, location, or truck type or a global energy company, choosing sources, means, and markets; strategy, choices, and decisions take place and their results drive growth (or lack thereof).

With digital transformation, the presence of strategy in business growth does not change. Growth is always about choosing new or better products and services, new or better customer interactions, or new or better ways of doing business. A strategy leveraging Digital Transformation is merely the newest, fastest, least expensive way to deliver growth.  Jeanne Ross at MIT/Sloan gives a strong definition of Digital Strategy as an: “integrated business strategy inspired by the capabilities of powerful readily accessible technologies like social, mobile, analytics, cloud, and internet of things and responsive to constantly changing market conditions.” (link)

Social and mobile are usually focused on new or better customer interactions. Analytics and cloud on new or better ways of doing business. And Internet of Things about innovative anticipatory capabilities based on pervasive connectivity and data gathering to delivers new or better products and services. But, the root of all of this is data. Social and Mobile customer interactions rely on data to and from social and mobile platforms to drive the new and better interactions. Cloud and Analytics drive new or better ways of doing business from data that is provided or enabled. And internet of things drives new products and services from the data that IoT provides and presents. Moreover, and maybe more importantly, social, mobile, analytics, cloud, and IoT together create more expressive data at unbounded volumes. Data is both the root and a result.

Getting a handle on data in business is not new.

However, harnessing data for digital transformation is new. Databases, and Data Warehouses, and more recently Data Lakes have made their mark and become established business capabilities. However, the recent advances in Artificial Intelligence have become a key capability for digitally inspired business initiatives. In AI, models need to be trained from datasets that need to be created, fused, and then run through models to train the models. Databases, Data Warehouses, and Data Lakes are not well suited or specifically designed to train models from created “virtual” datasets.

Indeed, while AI continues to capture the imagination of the public and rightly demands the attention of enterprises and businesses of all types, a recent KDNuggets article sums up the current situation nicely. “Academic papers are almost entirely focused on new and improved models, with datasets usually chosen from a small set of public archives. Everyone I know who uses deep learning as part of an actual application spends most of their time worrying about the training data instead.” https://www.kdnuggets.com/2018/06/improve-training-data-how.html. The article posts a picture that humorously describes the challenge with data in business (in this case Tesla) vs in Academia (side note, I hear from many academics that data is no less a challenge there as well).

Lisha Li from a presentation by Andrej Karpathy

Lisha Li from a presentation by Andrej Karpathy

Challenges in business with data

The first challenge with Business data is the oft-mentioned data silos. Data silos are viewed as a negative result of outdated systems and processes or the result of the creation of..... READ MORE....

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