Best Practices to Demystify Data Science for Business

by June 12, 2020 0 comments

Data Science

“How do you know the true potential of data to move your business?”

There has never been a better time to gain value from (your) data. More and more data are available courtesy IoT and Artificial Intelligence. Rapid advancements are made in terms of computing power and mathematical techniques. What’s more, “digital” and “data” have become the new trend and conversation starters. Calling data as the “new oil” or the “new gold” is not something to be missed, several technologies and businesses revolve around data. Thus, understanding data’s importance and realizing its untapped potential is a persistent challenge business stare at.

As the C-suite and technology team debate how to harness this data for their best professional interests, data-driven decisions and actions remain a strategic discussion topic in meeting rooms. The quest to achieve the “right data, for the right user, at the right time” has been the primary motto of business intelligence (BI) and data warehousing since time eternity.

When it comes to decision-making, information about your customers, partners, staff, and stakeholders are all data-oriented. Though in some cases, intuition is good, all the qualitative and quantitative facts well stored into silos of spreadsheets and applications are what you want to rely on for accuracy.

 

Breaking Data Islands and Data Silos

“It is no secret that data silos remain one of the most complexes yet well-kept stockpiles of intelligent strategies”

Businesses of all kinds whether large conglomerates or SMEs, experience data silos in some form or another. However, this data does not only increase in volume; but shows signs of tremendous richness and diversity as we talk of the three V’s of Big Data. Technology has made mankind step to a new era in which the physical world is becoming increasingly connected to the digital world courtesy smart IoT devices. Data in both structured and unstructured format is generated by everything around us, call it social media, interconnected devices, wearable technology, traffic sensors the list is endless. This mammoth data opens doors to richer insights into human and “thing” behavior.

The onslaught of new technology to break data silos and data islands has broken the traditional IT operating models in use. Today, an average enterprise runs on countless applications, and only a minuscule integrate. Real-time, on-demand information benefits everyone, but it comes at a cost to IT.

 

Blocker for Decision Making

Data silos create a myriad of problems and present a hiccup to decision making, which ends up acting as a roadblock to your business growth. Knowing exactly what they are and in what potential they can affect your team, and how to solve them makes all the difference.

The pains of siloed data are felt by nearly every industry. They create persistent issues such as redundancies between departments, an inability to grow or scale, and processes inconsistent information across the organization. Enter the savior-technology, with its new tools been developed for turning this flood of raw data into intelligent insights and eventually into strategic action. Machine learning, a term that encapsulates algorithmic approaches from statistical methods like neural networks to regressions, has rapidly advanced to break data silos and unchain data isolation much to business relief.

 

Demystifying Data Complexities

Analytic database platforms specifically designed to support advanced analytics and data discovery are much easy to deploy, load with data, and use. Offering dashboard-based information views, analytics, flexible data visualization, and more, Intelligent data offerings are spurring business users and functionaries to venture beyond the boundaries of IT management and try out the easy to access technologies themselves.

However, here is a catch- demystifying data, a business must commit itself to move boldly and strategically into the implementation of use cases curated to leverage the positives of technology. This means that not only business should focus on impact; it must strategize so that technology is not restricted to a single-use case. Rolling out multiple use cases across functionaries and orchestrating them to drive business from data requires a full tech-enabled transformation.

“Getting the first step, technical foundations correct is typically the easier one, the challenge is swimming across the data lake”

What is likely to be the bigger challenge is collating business goals in a bid to successfully implement new insight-based use cases. Enabling an organization to manage use cases across data siloes, to automate processes, impart change management across organizational hierarchy often requires a complex but necessary shift of organizational structure and culture.

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