Data Modeling – Turns Data into Opportunities

Companies always work religiously towards building an enterprise which is more than a business, and more of a living entity, always equipped for consistent and positive renewal and profitable growth. Business leaders are looking out towards building an organization which keeps on revitalizing to work in productive ways.

They dream of an enterprise, where learnings from data analytics can be implemented without investing huge dollars in building data centers. Reports provide actionable insights and even foresight to orchestrate futuristic events. Machine learning and artificial intelligence are more than terms and amplify human imagination. The overall business comes up with constant change and dynamics, making it the strength to operate.

This is no fairy tale. Nearly all Fortune 500 and Fortune 100 companies dreamt of it once, and now are successfully operating this way, walking the path of digital transformation. For these companies, everything is woven in and around data; which makes data modeling the first step towards digital transformation.

Data modeling aligns business with data

Data modeling is what helps organizations to unlock the value of its data, make it conveniently available to be shared with business stakeholders. If done appropriately, data modeling is the key to support data initiatives, in addition to the program of tomorrow and the day after and after. Also the cost involved tends to diminish when the company repeats and innovates against that data model to bring value to specific data initiatives.

And by opening the model so it can be understood by the appropriate roles in their respective terms, trust in the data grows. The growing trust in data makes companies use it more often, leading to increased efficiency and lower costs; all this is above and over the new opportunities that company data has to offer.

It is a must to understand that if digital transformation is an opportunity, it is a challenge too. Data modeling happens to be the toughest part of transformation, to become one of those data-driven enterprises. It is so because companies cannot manage what they can’t see or visualize, helping them overcome market challenges and attain business objectives.

For this, what is required is a blueprint of data, or say a detailed visual representation of company database, equipped with adequate information in different contexts for different stakeholders with a wide plethora of perspectives.

Data modeling to have a unified view of company data

Company data is generated from a variety of sources and eventually is stored in a variety of formats. Usually, conventional data can be considered to be structured, however; today’s data laced with clickstreams, social media and various other forms of unstructured data makes its management a tricky task. It truly becomes messy and difficult when it comes to taking a more data-centric approach to operations. This is then followed by a more harrowing challenge of storage of this data in a secure location.

No doubt companies have moved on to cloud from onsite databases, or to hybrid data architecture, but irrespective of the location or the form – they still need to see all their data to analyze it to make informed decisions for desired business outcomes.

Data modeling creates that accurate model of data assets, from structured or unstructured data, may it be in-house data storage facility or in the cloud, for that unified view of data. Actually, it is an assortment of activities including how and what data is collected, data is cleansed regularly followed with validation and categorization. All this resulting in integrated and graphical documentation of business data available to stakeholders to see business-critical information, irrespective of the location they are accessing it from to:

• Discover, standardize and document existing data sources for data visualization and data analytics
• Graphically design, deploy and integrate high-end data sources across distinct platforms
• Visually compare, analyze and synchronize data models with deployed data assets
• Align data modeling teams, processes, portfolios and lifecycle
• Implementing active data governance, metadata configurations and stakeholder feedback
• Assistance with self-service data model exploration, visualization, analysis and collaboration

Companies, in order to get more data-centric for competitive growth, can no more rely and survive only on few tinned reports. Gut instincts to make business decisions also have started failing miserably in a concurrent market and economic dynamics. It’s only the data that can help. They are required to become data-driven. Making data readily available and easy to use across the organization, to make it inherent and a trusted part of the decision-making process is the need of the hour.

Data modeling breaks down data silos, enhances quality and governance, and connects stakeholders for greater data fluency, accountability and collaboration. This is exactly where digital transformation starts, the first step in redefining business, markets and customer relationships.

Data modeling turns data into opportunities

The trick is to use data as a strategic asset. Gone are the days of realizing a return on investments, today it is all about return on opportunity. It increases considerably if you know how to bring that data to the business, making it conveniently accessible. IOT, social media, big data, data analytics all this leads to digital transformation – making it a fact of life.

Companies like Airbnb, Netflix and Uber were prompt enough to realize that data equals opportunity and ultimately they succeeded in establishing themselves as successful brands. The only challenge is “Do you know how to harness data & turn it into opportunities?”

The correlation between business-focused data management and business alignment first, flowed with technology infrastructure and profitable growth; is no more a rocket science and so C-suite and even CDOs are paying due attention to data management and business operations – simultaneously. Startups with clean data slates or a traditional brick and mortar company, all of them are required to capitalize on the opportunities that data present, to not only survive but thrive.