Quality analytics and cloud computing are the keys to maximum value extraction from data
“Data” – The word that is currently synonymous with the word “Colossal”!
Data and its complexities are growing exponentially in response to increasing mobile data transmissions, cloud-computing traffic, and the inclusion of IoT and AI in technological advancements. By 2025, IDC predicts the worldwide data market will reach 175 zettabytes. With enormous data generated, it is easy for enterprises to feel lost or overwhelmed. It’ll get hard for them to efficiently manage their data, analyze it and protect it from malicious attacks. This may result in enterprises feeling paralyzed by the lack of knowledge and hounded by the question, “Where to begin?”. The answer is simple – Organizations must begin by assessing if they are storing the right data at the right place and what they are doing to get maximum value out of it for organizational growth. Here are three ways to assess if your organization is on the right path towards creating an optimized and efficient data management ecosystem:
1. Are you storing enough of your enterprise data?
According to IDC, enterprises should store more of their data for three reasons:
The importance of big data transcends beyond how much data you collect and store. Instead, it is about how you use the data to add value to your business. Companies that use data effectively have a competitive advantage over those that don’t since they can make more informed decisions faster and more efficiently.
2. Where does your enterprise stand on its journey to extract value from stored data?
An enterprise collects data at every stage of its operations, including product development, manufacturing, supply chain, operations, sales, and customer service. The proliferation of data is transforming every company into a data company. Whether an enterprise is successful depends on the extent to which it uses its data to extract insights that help make smart business decisions.
According to a new report from Seagate and IDC, enterprise data collection is expected to increase by 42 percent annually in just the next two years. Despite this, substantial chunks of data remain untapped due to data management and security challenges. The report further states that a lack of solid data management techniques could result in enterprises hoarding their data instead of gaining value from the data.
Luis Gutierrez, COO of Data Dynamics and a veteran in managing infrastructure for some of the largest global financial and manufacturing companies, says that an enterprise’s understanding of their data is the biggest challenge. He adds that the awareness about data management is relatively new and organizations often don’t realize how much data they have and how critical that information is to their business. In his opinion, most enterprises are still at the early stages of understanding and extracting value from data. It’s only a matter of time before they realize that if they nurture and cultivate their data, they will have a tremendous amount of assets available to them.
Data is still a challenging topic for many enterprises, and their challenges extend beyond technology. Culture and operational challenges pose some of the biggest obstacles, including a lack of trust around data use, the inability to operationalize data for strategic use, and the absence of an enterprise strategy.
Based on a recent Forrester Consulting study, businesses that use data management tools to make decisions are 58% more likely to reach revenue goals than those that do not. Furthermore, data-driven organizations are 162% more likely to exceed revenue targets than laggards significantly.
3. Can cloud computing transform your organization’s data into information?
Two of the most disruptive technologies of the past decade have been cloud computing and big data. Adapting to these developments has changed how technology organizations operate and deliver value to their stakeholders. As organizations face vast volumes of data, they are increasingly turning to the cloud to handle storing, analyzing, and extracting insights. Cloud computing enables companies to analyze data in an extraordinary way to derive intelligence. From there, business transformation begins. It allows big data analytics to tap into structured and unstructured data to uncover business value.
Moving data to the cloud is crucial for Integrating disparate data sources. Here are three reasons how:
- Enterprises can break down data silos and foster more effective collaboration and more agile outcomes through cloud computing.
- Enable new business initiatives to generate new insights by leveraging unused data.
- Strengthen security by detecting a series of risky actions that can lead to ransomware attacks and preventing them at scale faster than traditional investigative techniques.
For example, cloud computing is an invisible force that makes healthcare operations possible amidst the army of life-saving machines. Using machine learning technology, cloud computing can run critical applications, analyze, and extract unstructured data, including physician and lab notes (typed and handwritten). Increasingly, healthcare businesses can extract value from data to support diagnostics, personalized treatments, imaging analysis, patient trend analysis, outcomes prediction, and automation.
The simplest way towards extracting maximum value from your organizational data – An Unified Data Management platform that analyzes, understands, applies intelligence, and acts.
With Data Dynamic’s Unified Data Management platform, enterprises can migrate their data securely to the cloud using policy-based automation. Furthermore, enterprises can make full use of the agility and cost savings offered by cloud computing. Utilizing our platform, enterprises can gain insights from data that will provide risk analysis for sensitive personal and business data to ensure compliance and security. Our holistic data management platform allows you to analyze unstructured data to extract patterns or insights that will enable you to make informed decisions about data governance.