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Unlocking the Power of Data Storage Solutions for Your Enterprise

StrategyDriven Organizational Performance Measures Article | Unlocking the Power of Data Storage Solutions for Your Enterprise

Introduction

In today’s fast-paced business world, data is the lifeblood of any enterprise. From customer information to financial records, enterprises depend on data to make informed decisions and remain competitive. Therefore, data storage solutions have become an integral part of enterprise infrastructure. In this article, we will explore the importance of data storage solutions, the benefits of integrating them, and how to choose the right solution for your enterprise’s needs.

Definition of Data Storage Solutions

Data storage solutions encompass a variety of technologies, tools, and platforms that businesses use to store, manage, and safeguard their data. These solutions may include conventional on-premise storage systems or intelligent cloud-based ERP system, offering a wide range of options to cater to the specific needs of each enterprise. 

Importance of Data Storage Solutions for Enterprises

The importance of data storage solutions for enterprises cannot be overstated. Efficient data storage solutions enable enterprises to:

  1. Improve data management
  2. Enhance data security
  3. Increase workflow efficiency
  4. Save costs on IT infrastructure and operations.

Overview of Benefits of Integrating Data Storage Solutions

Integrating data storage solutions can provide numerous benefits to enterprises, including:

  1. Cost efficiency
  2. Scalability
  3. Data security
  4. Efficiency and accessibility.

Benefits of Integrating Data Storage Solutions

1. Cost Efficiency

One of the primary benefits of integrating data storage solutions is cost efficiency. By using a centralized storage system, enterprises can reduce their IT infrastructure and operational costs significantly. For example, cloud storage solutions can eliminate the need for on-premise storage hardware and related maintenance costs.

Companies that have adopted data storage solutions have reported substantial cost savings. For instance, Siemens, a multinational conglomerate, saved $1 million in hardware and maintenance costs by switching to cloud storage. Cost savings from data storage solutions can be measured by evaluating factors such as IT infrastructure and operations costs, data management costs, and disaster recovery costs.

2. Scalability

Data storage solutions are designed to accommodate enterprise growth. As enterprises expand, the volume of data they generate increases. Therefore, it is crucial to have a storage solution that can scale with the enterprise’s needs. For example, cloud storage solutions offer virtually unlimited scalability, allowing enterprises to store and manage an increasing amount of data.

Companies such as Netflix and Airbnb have effectively scaled their data storage solutions to accommodate their rapid growth. When choosing a data storage solution, enterprises should consider factors such as data volume, performance, and latency requirements to determine the most suitable solution.

3. Data Security

Data breaches can have severe consequences for enterprises, including financial losses, reputational damage, and legal liabilities. Data storage solutions can enhance data security by providing features such as encryption, access controls, and data backup and recovery.

Several companies have prevented data breaches by implementing data storage solutions. For example, Dropbox, a cloud storage provider, prevented a security breach in 2012 by implementing two-factor authentication. When choosing a data storage solution, enterprises should consider security features such as data encryption, access controls, and compliance with industry standards and regulations.

4. Efficiency and Accessibility

Data storage solutions can improve workflow efficiency and accessibility by providing real-time data access and collaboration tools. With a centralized storage system, enterprises can reduce the time spent searching for data and collaborating with team members.

Several companies have reported increased productivity and workflow efficiency after adopting data storage solutions. For example, the Bank of America reported a 95% reduction in data management time after implementing a centralized storage system. When selecting a data storage solution, enterprises should consider features such as real-time data access, collaboration tools, and integration with existing workflows.

Enterprises to Adopt Data Storage Solutions

In today’s data-driven business world, enterprises cannot afford to ignore the importance of data storage solutions. The benefits of integrating data storage solutions far outweigh the costs, and enterprises that fail to adopt them risk falling behind their competitors. Therefore, we urge all enterprises to evaluate their data storage needs and consider integrating data storage solutions to unlock their full potential.

FAQs

1. What is the difference between cloud storage and local storage?

Cloud storage refers to a remote storage service that allows users to store and access data from anywhere with an internet connection. Local storage, on the other hand, refers to a physical storage device located on-premise or at a specific location.

2. How much data can be stored in a data storage solution?

The amount of data that can be stored in a data storage solution depends on the specific solution and the storage capacity it offers. Cloud storage solutions typically offer virtually unlimited storage capacity, while on-premise storage solutions have a finite storage capacity based on the hardware used.

3. Is it necessary to have multiple data storage solutions for an enterprise?

It depends on the size and complexity of the enterprise. Smaller enterprises may be able to meet their data storage needs with a single solution, while larger enterprises may require multiple solutions to accommodate their diverse data storage needs.

4. What are the costs associated with integrating data storage solutions in an enterprise?

The costs associated with integrating data storage solutions vary depending on the solution chosen, the enterprise’s size, and its specific data storage needs. Some of the costs associated with integrating data storage solutions include hardware and software costs, implementation costs, and ongoing maintenance costs.

5. How secure are data storage solutions?

Data storage solutions can enhance data security by providing encryption, access controls, and other security features. However, the security of a data storage solution depends on the specific solution and the security measures implemented by the enterprise. It is essential to choose a data storage solution that meets the enterprise’s security requirements and complies with industry standards and regulations.

Conclusion

Data storage solutions, including SAP ERP solutions, are crucial for enterprises to effectively manage and protect their data. The benefits of integrating data storage solutions include cost efficiency, scalability, data security, and efficiency and accessibility. Enterprises should carefully evaluate their data storage needs and choose a solution that aligns with their growth trajectory and data security requirements. By adopting data storage solutions, enterprises can achieve significant cost savings, improve workflow efficiency, and enhance data security. Therefore, it is essential for enterprises to consider integrating data storage solutions, such as ERP solutions, as part of their overall IT infrastructure.

4 Winning Strategies for Adopting Big Data Analytics

StrategyDriven Organizational Performance Measures Article | 4 Winning Strategies for Adopting Big Data AnalyticsIf you’ve decided that now is the time for your business to make the transition to Big Data Analytics; great choice. Not only will you be able to analyze and process much more relevant information than before – you’ll also be able to begin putting it to good use as your business ambitions expand. Here are 4 winning strategies to help you with adopting BDA and take your company to the next level.

What is BDA?

In the simplest terms, it’s a service that allows the user to process huge amounts of data and then use this information for analysis purposes. The only drawback is that the greater the volume of data, the more likely errors and false readings are. With that being said, there are parameters that can be set to reduce the chance of this. With the above in mind, let’s begin with our strategies.

Turn your data into intelligence

The first strategy on our list is a pretty straightforward one, as it relies on what BDA does best – collecting data and compiling it for easy navigation. By embarking on a new campaign, any data that you use can be refined and then processed in an orderly fashion. With this data, you can then gain insights into a particular demographic, a target audience, the potential for conversions, and much more. The more you know, the better equipped you’ll be moving forward.

Cost reductions

Another great way to adopt big data analytics is in an effort to reduce your costs. The data being processed doesn’t only have to be external – it can be internal too, meaning that you could analyze the performance of your own business and see where specific costs can be cut. This can also be done via data analytics consulting, whereby you hire an expert to analyse the information presented and then create a report for you to use to reduce expenses.


Developing products with greater insight

If you’re in the process of creating a product, or if you’re about to introduce yours to the market, what more efficient way to identify key behaviors from potential customers than with BDA? By performing a detailed evaluation and then reading results from a chart, you can see where to dedicate your sales and marketing efforts, ensuring the potential for maximum reach.

Market insights

Complimenting point 3 above, BDA also allows detailed market insights including trends, customer behavior and patterns, and other important aspects to be considered. Adopting BDA in this way can actually force a business to pay attention to the finer details, albeit in a gentle, efficient way. The more insight you have into a market, the more likely you’ll be to achieve your aims.

Final thoughts

And there you have it – 4 great ways to adopt and utilize Big Data within your business in a way that promotes productivity, enhances the possibility of profit, and maximizes your chances of understanding your target demographic. Once adopted in full, you’ll quickly begin to see why so many people are turning to the potential of BDA.

Developing Performance Measures

StrategyDriven Organizational Performance Measures Article | Developing Performance MeasuresA performance measure is a quantification that provides objective evidence of the degree to which a performance result is occurring over time. There are many definitions of performance measures, but this one accurately and broadly elucidates the meaning of the concept. In long term-projects, even short-term ones, it is imperative to have a system through which results are measurable. For this reason, performance measures are quite necessary.

Specific Advantages of Performance Measures

  • Productivity Increase: One great advantage of having performance measures is that it increases productivity in any given task or project, especially in a team.
  • Setting Standards: Performance measures can be instrumental in setting standards. For instance, by measuring performance, a person would know how much they can achieve over a given period of time. The assessment of this ability can help set the standard the next time the said task is performed in the same organization or a different one.
  • Determining Strength and Weaknesses: In an organization, setting up measures to track the performance of different tasks will help to determine which tasks employees are better at. This is a great way to foster specialization and division of labor; ultimately leading to effectiveness and productivity.
  • Supports Communication: Having metrics to measure performance ensures that individuals in an organization are more transparent and work as a team.

Types of Performance Measures

There are different types of performance measures. All these measures could provide a relatively accurate description of results. They can be categorized into the following: input measures, output measures, outcome measures, efficiency measures, and explanatory information.

  • Input Measures: Input measures comprise the resources consumed by a project such as the money and time spent. For instance, if the employers in a firm work an eight-hour shift daily, it makes up part of the input measures.
  • Output Measures: Output measures can be very clear. They simply depict the amount of work that has been executed as a result of the input. Comparing the present output with the former one can be instrumental in measuring standards and how employers work in different circumstances. Output measures usually consist simply of numerical values.
  • Efficiency Measures: Efficiency is depicted by the amount of work performed compared to the number of resources used in doing the work. It is expressed in units. Efficiency measures are not always very effective because there are usually a lot of factors affecting performance other than the variables involved in efficiency measures
  • Explanatory Information: Explanatory information simply involves other factors that affect the performance of an organization in any given situation. These factors might include environmental factors, incentives, the motivation of workers, etc.

StrategyDriven Organizational Performance Measures Article | Developing Performance MeasuresProcesses and Steps involved in Creating Performance Measures

The process of developing performance measures can involve many steps. Many different experts have propounded several theories to achieving this result. Here are some of the most important activities to engage in to arrive at a reliable measurement of performance in the long run.

1. Collecting Stakeholder Information

The developmental point of collecting performance postulates that the information and opinions of the stakeholders involved in the process are collected. Cambridge Dictionary explicitly defines a stakeholder as a person such as an employee, customer, or citizen who is involved with an organization, society, etc., and therefore has responsibilities towards it and an interest in its success. The list of stakeholders includes the following people:

  • Members of staff at all levels.
  • The customers or clients of the organization. If it is a public office, the information should be collected from the people being served.
  • Policymakers; are the people at the helm of affairs whose decisions affect the running of the organization.
  • The financiers of the service or the organization.
  • The evaluators of the activities of the organization.

This step is necessary because your stakeholders are the people who are most interested in the activities and success of your organization. Their opinions and suggestions are important to the running of the organization. Also, collecting stakeholder information helps you to know what they want from you. Through this, you can streamline your objectives and measure performance according to them.

2. Incorporate Various Types of Performance Measures 

To arrive at a holistic evaluation of the performance of the people/persons in a task, the types of performance measures listed above should be incorporated into your performance measurement. Nevertheless, this depends on a few other factors such as the type of project being executed. For instance, a holistic approach is not paramount if the task being carried out only affects one small unit of the organization.

3. Promote Top Leadership Support 

There is a high tendency that lower-level staff in an organization will not be in support of performance measures. Therefore, the topmost leaders have to regularly encourage the use of performance measures and bring the other staff members on board. If feasible, the leaders should also be subject to performance measures like the mid-level staff and other personnel. This exemplary effort will ensure that other staff members feel more comfortable in the use of performance measures to evaluate their work.

4. Establish Long-term Goals and Objectives 

Goal-setting is arguably the most important part of developing measures. What is the end goal of the project that your organization is involved in? By identifying these, you can develop measures that particularly check for them. Most projects in which performance is measured are usually long term. Hence, it is even more difficult for all the people involved to keep sight of the end goal. This can be made easier by documenting the objectives so that they can be read regularly by all the stakeholders.

Long-term goals can be documented in the form of a mission statement. The mission statement should be documented in clear and concise terms to ensure that all the parties involved understand it.

5. Establish Short Term Goals to Help Attain the Long-Term Goals 

Long-term goals are relative. Achieving long-term goals in some situations could take a few years. Therefore, special attention should be given to short-term goals. Firstly, the short-term goals should be formulated in line with the long-term goals. The achievement of short-term goals regularly by all the people involved in the process builds up to the achievement of the long-term goals. Again, the short-term goals have to be in line with what is hoped to be achieved in the long run.

In setting and matching goals, we can depend on the SMART acronym. SMART stands for specific, measurable, achievable, relevant, and time-bound. Professionals from different fields have used this acronym in many different situations and it has proven effective. If your goals fulfill the criteria in the acronym, there is every tendency that it is feasible.

6. Establish Performance Targets 

This is achieved by taking a look at past performances and comparing them to the present. In developing performance measures, it is important to have already set standards. These standards are gotten from previous tasks and projects.

7. Create a Simple Approach 

This step involves the following activities:

  • Ensure that your measures match your goals and objectives.
  • Take all the time needed to perform tasks.
  • Keep the number of measures you use at the lowest.
  • Decide what level of performance defines success.
  • Ensure that you possess enough resources for the project.

Conclusion

Developing performance measures can be very advantageous, especially in the long run. Nonetheless, it is important to ensure that the performance measures we use are effective and result-oriented. Note that the use of performance measures can also have some disadvantages.


About the Author

StrategyDriven Expert Contributor | Tiffany HarperTiffany Harper is an experienced writing guru who’s been working in the B2B sector for several years now. She loves to share her thoughts through blogs and social media. For her love of writing, she also provided some consultation while working with dissertation writing services from Assignment Masters.

Managing the Power and Promise of High-Performance Computing

StrategyDriven Organizational Performance Measures Article | Managing the Power and Promise of High-Performance ComputingAs we battle global threats, from COVID-19 to global warming, achieving new heights in data analysis will enable new solutions to world problems. The next major milestone in High Performance Computing (HPC) is “exascale”: over one billion billion calculations per second. These new exascale systems combine the latest technologies in AI, engineering and science, to achieve performance faster than any supercomputer before. But perhaps most surprisingly, these computers will use technology from videogames to achieve this goal.

In 2019, Hyperion Research predicted 26 exascale and near-exascale HPC systems to be deployed between 2020 and 2025, with spending increasing to $39 billion in 2023. Hyperion also estimated that HPC applied to artificial intelligence (AI) would experience an almost 30 percent compound annual growth rate. The largest HPC systems are being created by government institutions and referred to as Exascale systems. Managing this computing power will pose a challenge.

Trip Down Memory Lane

Companies have been using a variety of processor architectures over the years. In the past, normal CPUs have been able to achieve high performance if enough of them are connected together in a supercomputer. But, over the last few years, graphics processors (GPUs, a technology from videogames) have become increasingly the only way of achieving very high levels of performance.

Companies realized that none of these approaches were viable in the long term, especially in an era when many new processor architectures were available for accelerating Artificial Intelligence (AI) functions and increasingly demanding benchmarks were required. CUDA was widely adopted and providing an excellent solution, but it was not an open standard and therefore an alternative was required which would provide all the benefits of CUDA but with an ecosystem of developers and multiple hardware suppliers.

Forced Standard Created ‘Square Pegs’ Dilemma

Historically, supercomputers like Jaguar and Titan used a mix of CPUs and GPUs to reach high levels of performance in a supercomputer. But the programming model suffered loss of separation of concerns and could not remain stable. The problem was, building a mix of CPUs and GPUs in a supercomputer (called “heterogeneous processing”) creates. So a new standard was created. But with heterogeneous computing, one can’t simply add a few annotations (called “pragmas”) in a few performance-critical areas of the software to solve inherent problems. One needs to think holistically to drastically improve performance and programmability. OpenMP and OpenACC, which were originally designed for parallel computing using multi-core, were heroically adapted for heterogeneous computing using the OpenMP pragma model but it was weak in the areas of separation of concerns, error handling, and object oriented resource management, which were in demand by the newest generation of code. The CUDA programming model failed to meet expectations because it was proprietary to Nvidia’s hardware and locked enterprises into a vendor.

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Clearly Defined Standards Take a Stand

There is a momentum of movement towards SYCL, a Khronos® open-standard alternative, providing many of the standard C++ programming needs of scientists and other programmers. Companies like Codeplay have, in effect, reset the playing field. By clearly leading the definition of standards, companies can now use the same standard programming model with non-Nvidia processors, as well as Nvidia GPUs. This sets a new high-water mark for standardized heterogeneous computing, ideal for enterprises that employ accelerated processors. The goal is to leverage the open standard, which has long been a requirement of high-performance computing as their workload can last 20 years while their hardware can change every five years.

Agile HPC Software Solutions

Codeplay’s Acoran® platform integrates all industry-standard technologies needed to accelerate complex software. It provides platform-level integration between processors, open-source frameworks, and standard programming models that finally allow users to develop their own custom accelerated software.

Acoran combines the open programmability and a wide feature-set of proprietary solutions like NVIDIA’s CUDA, with the open-source, future-proof, standards-based flexibility of the Intel supported oneAPI. This allows Acoran to be easily adopted by processor vendors for new accelerator processors as well as software developers seeking high performance for their innovative algorithms.

The world of HPC is rapidly expanding. Some will adopt an in-house approach; others will seek refuge in cloud-based solutions. But the need for standards-based easy-to-integrate solutions will always remain a top priority.


About Codeplay

A world pioneer in acceleration technologies, Codeplay Software continues to develop effective tools that enable complex software to be accelerated using graphics processors. Codeplay has long recognized the need to address a market looking for standards-based solutions — solutions that are easy to integrate between multiple vendors. The company works with the world’s leading technology businesses to build advanced intelligence into devices ranging from smartphones to self-driving cars. For more information, visit www.codeplay.com.

The Significance of Data Optimization During Covid-19 Pandemic

StrategyDriven Organizational Performance Measures Article | The Significance of Data Optimization During Covid-19 Pandemic | Data Optimization | Data ManagementUntil recently, very few CEOs, IT, or marketing professionals would have put ‘data optimization’ high on the list of agenda items that keep them up at night. These days — and by my estimation — this notion has become a top priority for the majority of businesses. Given the impact of events surrounding COVID-19, I view this not a matter of if, but when decision makers also arrive at this conclusion.

The simple fact is that businesses need to be able to build trusted relationships with their customers beyond the physical spaces represented by storefronts and square footage. As ironic as that sounds, what distinguishes data is its human factor. Interpreting and making decisions based on data during a time when competitors are trying to capture the attention of their consumers is vital.

Today, amid a global pandemic and subsequent overhaul of how businesses access and interface with their customers, we find ourselves suddenly competing on a level playing field that is the attention of a phone, computer, or TV. No foot traffic, no event, launch, or experience — just time and attention on a screen, and it’s the ones who have optimized their data who are winning.

Here are a few tentpoles to consider points of entry towards optimizing your data:

The Customer

The modern customer has high expectations and demands that enterprises strive to achieve — at all costs. A business with quality data optimization services has comprehensive information that is customer-centered, dynamic, and always available.

As a result, there is a real-time ability to address all customer demands without going through a complicated, costly, or time-consuming process. Naturally, as customers become more aggressive in having their requirements met, your business stays a step ahead of competitors, when it comes to availing quick and accurate solutions. The most critical aspect of better data management is the reduction of inefficiencies in operations that cost businesses as much as 25% of their revenue. This is because enterprises with better control over their data reduce the potential of making mistakes. As a result, their trustworthiness among customers in any niche industry grows, and they become seen as market leaders.

Direct Sources

Long gone are the days when e-commerce strategy meant focusing only on SEO. Mike Ewing, a Customer Success Strategy & Operations Manager, writes on Hubspot, ”if you rely on free/direct sources of traffic, you are fighting shared losses. Direct has gone from 75% to 9% over the last ten years, while e-commerce has been growing 15-25%.”

Today, you need to find a way to seamlessly integrate direct traffic, transaction data, demographic data, paid search, comparison shopping engines, marketplaces, mobile, and social media. That’s a lot! Each medium comes with its own tools, database, and strategies — only by combining all can your business stay on top of your competition… and crush your topline goals and quotas.

Bottom line: Your products and services should be where your clients are.

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Speed

The data modern enterprises depend upon may have many different sources and a variety of structured and unstructured formats. In many cases, the data will contain inaccuracies, inconsistencies, redundant information, or other anomalies that make it unnecessarily difficult to access critical information in a timely and comprehensive fashion.

The data optimization process makes use of sophisticated data quality tools that help to access, organize, and cleanse data — whatever the source — to maximize the speed and comprehensiveness with which pertinent information can be extracted, analyzed, and put to use. That enhanced availability of critical information provides businesses with significant benefits.

Data optimization helps business leaders understand and improve their business processes so that they can reduce the wastage of time and money. Consider the information age, a time and place where consumers expect to get fast, accurate, and comprehensive information from the business they are dealing with.

Embracing Data

Amid the panic and unrest of a rapidly changing COVID-19 environment, business leaders in the trenches must lean in to leverage all tools to make themselves more digitally enabled… if for no other reason than to maintain their relationship with their customers during times when human contact is not an option.

We must all consider new ways to bring the human factor into decisions around data optimization. The time is now.


About the Author

Megan Silva is a data optimization leader and advocate. Over the course of her 15-year career in data, Megan has led numerous business and process improvement initiatives, with an emphasis and focus on increased capabilities and decreased costs. She is best known for her leadership on measurable and scalable results, defining customer journeys, aligning content for automated campaigns, and improving contact and data strategy. Megan holds a Master of Industrial Labor Relations from Cornell University and a Bachelor of Science from the University of Wisconsin-Madison.