As organizations of today grow and evolve, so too are data volumes. Instead of throwing away old information, structured and unstructured data alike are funneled into enterprise data hubs, but often without the essential tool for keeping this data in order: metadata.
The struggle to manage information within the big data landscape is as complex as the digital workflows it supports. This landscape includes the internal ecosystem and the wider geography of partners and third-party entities. The complexity of all of the available data is compounded with the increasing rate of production and diversity of formats.
Data assets are critical to your business operations — they need to be discovered at all points of the digital lifecycle. Key to building trust in your data is ensuring its accuracy and usability. Leveraging meaningful metadata provides your best chance for a return on investment on the data assets created and becomes an essential line of defense against lost opportunities. Your users’ digital experience is based on their ability to identify, discover and experience your brand in the way it was intended. Value is not found — it’s made — so make the data meaningful to you, your users and your organization by managing it well.
We hear a lot about big datas ability to deliver usable insights, but what does that really mean? We do know, big data is behind countless achievements in everything from science to commerce. The true value of harnessing big data is almost limitless. From predicting buying behaviors, to intelligence-driven innovation, to finding totally new opportunities that could transform your business. Whatever your goal, start with a vision, open your mind to find opportunities you never knew existed.
How can you ensure that you are managing your data as a strategic asset? What role does data governance play? What industry trends are impacting the way data is being managed?
What insight can we get by looking at companies that lead the way in using data and making it actionable. Apple, Amazon, Google, Facebook, Netflix and Pandora have upended entire industries by analyzing and acting on only the data generated by the 10 billion devices connected to the Internet and mostly used by people. With the IoT predicted to connect 50-100mm devices by the end of the decade, it only increases the complexity discovering smart, actionable data.
It is this data that you will need to store, manage and extract meaning from if you want to gain meaningful business insights. Data governance will need to be in place and well managed to ensure the data being collected can be analyzed real-time by the ever-improving algorithms thereby enabling more precise customer insight resulting in more personalized experiences for customers. The precise analyses might result in a mobile app that guides customers to parking spaces near your store rather than a competitor’s, based on a historical turnover at Internet-enabled parking meters. Or it might underpin a corporate app that orders inventory for neighborhood drugstores based on usage reports from local smart insulin monitors, combined with area Web searches for cold remedies. All more than possible because of smart sensors in almost everything we buy and use, all connected and generating, even more, data that will feed the algorithm and rules engines that will decipher new trends in real-time.
What role should Metadata Management play? What are the experts saying?
Gartner states, The growing need for organizations to treat information as an asset is making metadata management strategic, driving significant growth for metadata management solutions
Gartners Assumptions Through 2018, 80% of data lakes will not include effective metadata management capabilities, making them inefficient.By 2020, 50% of information governance initiatives will be enacted with policies based on metadata alone.
From Forrester- The Foundation for Data Governance
Metadata management is the foundation for data governance, management, and use. But despite this, firms have a spotty record of collecting, harmonizing, and managing the metadata inherent in their business. Neglect may have been acceptable when a business’ data was generated and used internally and IT was the intermediary between business need and the data itself but not anymore. The explosion of types and sources of business data and the pressure on business to make a broader range of decisions on this data have raised the bar for metadata management. Metadata management solutions that started several years ago primarily around modeling must now evolve to better support a changing business and data landscape.
From Capgemini
In a world of connected objects and people, data can provide organizations with the foundation for every decision. But more data often creates more questions. Metadata Management solutions ensure that business data is clearly understood and consistently used across your company.
Key reason Chief Data Officers fail
Lack of tools to support the Chief Data Officer, including an enterprise metadata repository. One of the most important tools needed to effect required company-wide information management changes by financial service CDOs is the enterprise metadata, or knowledge, repository. This application captures, manages and presents critical business data from semantic definitions to consumer roles and responsibilities with respect to the information stored across the organization. Without such a tool, the CDO function is greatly compromised in its ability to rationalize and manage information at an enterprise level. Most large financial institutions have yet to deploy a standards-based business metadata repository and are, therefore, significantly behind in their efforts to rationalize their data at a company level.
From Deloitte
The path to a data-driven organization can only be achieved when users trust data and there is ownership and accountability to x bad data. Organizations can have the latest data management and analytics tools in the market and can have the fanciest dashboard for leaders to make decisions. However, these things will not bear fruit if the users do not trust the underlying data and if there is no accountability to x the bad data. An effective data management foundation will ensure that data is clean and evergreen and that there is data ownership by business leaders.
Dealing with Risk Management and Regulatory Compliance
If managing your enterprise data as a strategic asset doesnt get your attention maybe risk management and regulatory compliance will. In areas where risk management and regulatory compliance are a necessity, data governance is no longer a choice, it is a requirement. Regulators demand visible insights into risks and transparent audit trails that demonstrate compliance. Failing an external audit may spell disaster, both in financial terms and loss of reputation. An organization must know, at all times, what is happening to its data and how the data is moving and morphing from its inception to every destination.
Moving Forward
To date, data governance and metadata management have taken a back seat to the many new technologies and data sources that have come along this past decade. However, with the growing volumes of data and the inclusion of many semi-structured data sources, companies cannot afford to ignore this critical component of enterprise architecture. The time to adopt data governance is now, not down the line when some regulatory audit exposes the chaotic corporate data resource for what it has gradually become or when data has become mismanaged to the point where it is no longer trusted. As I have stated in many of my blogs. Will your company lead, follow or even become irrelevant in the coming years? It is not too late to make that choice, but in the next few years you wont have that option.
