#intelligent data

On most econometric models, the probability of a recession has now increased from 30% to around 60%.

The sense of an approaching catastrophe in the market is forcing businesses to take hasty, imprudent actions. Spending is cut too far, new initiatives are put on hold, and staff members are abruptly fired. Business executives are worried about the unpredictable nature of the future while attempting to maneuver through a potential recession.

Data may reduce a portion of this tension.

When the economy struggles, an organization’s most precious asset provides actual value. To maintain business stability and beat the repercussions of the recession, businesses must focus on using data to improve operational efficiency and productivity instead of taking drastic measures. Using historical data to uncover trends and insights and analyzing current data to understand the ongoing market and customer behavior will ensure profitability and create a competitive edge.

Here are the top five ways how.

Improving processes and workflows

Using internal data to identify the tasks that are operating as they ought to and the tasks that squandered time and money is one technique to develop an effective workflow. Dynamic management of processes can be achieved at all business levels, and tasks based on performance can be initiated automatically using data analytics. By assisting managers in evaluating the efficacy of current workflows, examining the results of the processes, automating new workflows, and continuously improving them, data analysis contributes to better company management. Data also enables leaders to assess whether any processes are cumbersome, expensive, or difficult to use and helps them speed up their digital initiatives from difficult/error-prone manual workflows to optimized/automated procedures.

Reducing waste and inefficiency

Operational efficiency and productivity are something that every company strives for. After all, who wouldn’t want their employees to work smarter, not harder? One way that companies are beginning to achieve this goal is by taking a data-driven approach. By analyzing the data generated by their business operations, companies can identify areas where there is room for improvement. This could be anything from finding ways to reduce waste and inefficiency to increasing communication and collaboration between departments. Businesses, for instance, can learn more about their data by using content and context analysis. This data can be further categorized as cold and hot, ROT, dark data, and sensitive data based on the knowledge incurred about the data. Businesses can optimize their data storage processes based on the kind of data by putting cold data in inexpensive object storage. Additionally, enterprises can reduce redundancies and duplication by consolidating multiple data lakes into one centralized data ocean.

Increasing transparency and communication

Enterprises can save time, uncover more insights, and make better decisions by rethinking how organizations distribute and consume data. They can democratize data by making it accessible to all users-both technical and non-technical-in order to gain a 360° view of

their customers, foster innovation, enable seamless hybrid working, and improve customer

experience. Communicating insights and sharing them across different departments for better decision-making will help achieve effective data interoperability, democratization, and literacy.

Ensuring accuracy and quality

Monitoring processes and tracking KPIs in real time can help enterprises improve process accuracy and quality. As a result, deviations from the norm can be identified and addressed quickly to maintain quality. Data helps to track process metrics, identify trends, spot gaps quickly, and take steps to rectify them. Additionally, analysis of historical data can reveal patterns or trends that may indicate future challenges, as well as remediation measures that have proven to be successful. Consistently implementing all of these steps help increase quality, efficiency, and productivity.

Tracking progress and productivity

Data can also be used to assess the results of different productivity initiatives and determine the most effective ones. Using this feedback, existing programs can be refined or adjusted, and new ones can be designed to increase productivity even further. In addition, data can be used to track employee performance, identify areas where they may need additional training or support, and initiate training programs accordingly. Data can help enterprises boost operational productivity as well as upskill employees.

Here’s an example of how a Fortune 200 bank improved its overall operational efficiency and lowered its total cost of ownership by 78.7% with Intelligent Data Storage Lifecycle Management

A Fortune 200 bank had three existing file storage applications and two object storage applications. They were suffering from high storage costs because they were underutilizing object storage and piling more data on file storage. Data Dynamics enabled them to optimize their total cost of ownership by intelligently moving data from file to object storage. Here’s how.

1. The bank had a total cost of ownership of 80.72M for 57,679 TB of data on file storage and 13.46M for 26,393 TB of data on cloud object storage.

2. They used only 53% of their total usable file storage and paid a surplus of $26.38M yearly for unused storage capacity.

3. The average cost of file storage per TB was $1,333, whereas it was $475 for cloud object storage, i.e., 64% lower than file storage

4. The objective was to move data from file storage to cloud object storage to reduce costs, enable higher capacities of usable data, and ensure pay-as-you-go pricing

Data Dynamics helped the organization realize a cost saving of 79.2% in one year with intelligent data management.

For every TB moved to cloud object storage, the bank could save $858 and increase total usable data capacity by 29%.

Proactive analysis of data on an ongoing basis

Policy-based ‘Intelligent’ tiering (local and cloud)

Full transparency on the physical and logical location of data

Avoid new hardware purchases

Massive carbon reduction impact (ESG value addition)

Large reduction in data center footprint

Staying afloat in volatile economic times requires effective data management.

Data Dynamics is a leading provider of enterprise data management solutions, helping organizations structure their unstructured data with their Unified Unstructured Data Management Platform. The platform encompasses four modules- Data Analytics, Mobility, Security, and Compliance. Proven in over 28 Fortune 100 organizations, the platform uses a blend of automation, AI, ML, and blockchain technologies and scales to meet the requirements of global enterprise workloads. With Data Dynamics, enterprise customers can eliminate the use of individual point solutions with siloed data views. Instead, they can utilize a single software platform to structure their unstructured data, unlock data-driven insights, secure data, ensure compliance and governance and drive cloud data management.

Following are our five most significant differentiators that help leading organizations thrive in an increasingly volatile environment:

A platform approach to data management vs. competitors with ‘single value’ tools

Multipetabyte and multi-location enterprise scalability

Insights into enterprise data to enable informed decisions — What and where is the data? Who has access? Is it secured and compliant?

Intelligent, compliant, and secured data migrations

A customized deployment based on the unique requirements of each client

In-year ROI on software investment

Ultimately, the company’s vision is to help enterprises achieve data democratization so that users, no matter their technical background, can instantly access, understand, and derive maximum insights from unstructured data sprawls.

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