Data management is more important than ever as it demonstrates the value of analytics in allowing a company to make more informed decisions in real-time, ultimately benefitting its bottom line.
But as data management evolves, companies need to implement an effective data management plan or risk redundancy.
To sum it up, data management can be used as a tool for innovation development and identifying patterns in information that humans are likely not to see.
In a few years, data management will become even more automated with a move to machine learning and artificial intelligence (AI) operations that will provide mission-critical data insights.
The future of data management will facilitate prescriptive business intelligence (BI) with additional real-time analytics, giving companies the ability to become even more agile.
Many organizations are already developing future-ready products. Looking at the automobile industry, some companies are creating a sustainable transport ecosystem by connecting electric, autonomous vehicles and gathering real-time data that informs teams of faultiness or any issues that arise.
However, the reality is most businesses only scrape the surface of the data available to them. Breakthroughs will come from companies that master the full potential of data to unleash the opportunities the digital economy provides. This begins and ends with an effective data management plan which brings several benefits to the table.
According to a Forbes, 95% of businesses need to manage unstructured data, with over 40% of companies mentioning they have to do so on a regular basis.
Any effective data management plan needs to take into account unstructured data. One of the best ways to do this is to make use of powerful metadata to turn unstructured data into objects that can be easily managed and governed. As a result, companies are provided with data mobility and improved data governance.
Automated metadata enrichment
Data is often lost to a business because they are unable to obtain insights in a simple and timeless manner.
Therefore, automated enrichment is vital as it shines a light on dark data, enriching it with valuable metadata to help simplify data management while adding value to data that at first glance held none. As a result, companies are provided with data mobility as well as improved data governance and compliance.
Legislation and regulations are changing the way businesses handle, manage and store customer data, such as the General Data Protection Regulation (GDPR) and the Protection of Personal Information (PoPI) Act.
Simplifying compliance while helping companies stay on the right side of the law, data management also ensures organisations meet policy regulation on public interest as consumers are becoming increasingly concerned with their personal data, worried about who has access to it and where it is being stored.
Companies need to manage data, maintain their quality while enabling regulatory compliance through data governance.
Data governance sets the blueprint when it comes to managing data assets which include several layers such as the operational framework, architecture and processes.
According to a study by Forbes Insights, strong data governance also enables BI. So, by having a sound data governance strategy in place companies will see improved returns from their BI investments.
By implementing an effective data management plan compliance is simplified while intelligent data governance provides a single, simple platform that extends across the private and public cloud, reducing the costs and complexities of data governance.
For any company, it is of the utmost importance to secure all data assets. Companies need to make data as secure and tamper-proof as possible.
An effective data management solution archives a business’s data so to protect it from hackers, natural disasters, software and hardware malfunctions, as well as a loss of human error. Really, a sound data management plan reduces risk significantly.
As the world is creating and consuming data at unprecedented rates, data management software is essential and brings added value to a business.
Key to understanding data is by pulling all disparate data sources into one centralised location, so businesses can view it, understand it and analyse it to make quick, informed decisions. Something Pentaho offers.
For example, Nasdaq OMX which manages over 10 billion rows of financial information every day, with 15 million trades and one billion messages daily was looking for new ways to gain better insight into the equity market to provide better pricing models. And since reports were manual, the company had no way of evaluating daily activity.
Leveraging Hitachi Vantara’s Pentaho solution provided Nasdaq OMX with predictive analytics by bringing in historical data while gaining the ability to scale and handle large volumes of data. Plus, with big data integration, the solution provided the company with valuable data-driven insights.
Other solutions within the Hitachi Vantara ecosystem can plug into Pentaho. This includes the Hitachi Content Platform, metadata enabled object storage solution and Hitachi Content Intelligence which provides companies with the ability to make their valuable corporate data fully searchable, while categorising and informing the business on the status and location of their data.
Hitachi Content Platform also provides organisations with the ability to view who within the business has access to specific data, allowing them to either grant or limit access accordingly.
Article Written by Alasdair Parsonson, Technical Expert at Data Intelligence for Hitachi Vantara