BIG DATA MANAGEMENT
Article | February 18, 2021
While digital transformation is proving to have many benefits for businesses, what is perhaps the most significant, is the vast amount of data there is available. And now, with an increasing number of businesses turning their focus to online, there is even more to be collected on competitors and markets than ever before.
Having all this information to hand may seem like any business owner’s dream, as they can now make insightful and informed commercial decisions based on what others are doing, what customers want and where markets are heading.
But according to Nate Burke, CEO of Diginius, a propriety software and solutions provider for ecommerce businesses, data should not be all a company relies upon when making important decisions.
Instead, there is a line to be drawn on where data is required and where human expertise and judgement can provide greater value.
Undeniably, the power of data is unmatched. With an abundance of data collection opportunities available online, and with an increasing number of businesses taking them, the potential and value of such information is richer than ever before.
And businesses are benefiting. Particularly where data concerns customer behaviour and market patterns. For instance, over the recent Christmas period, data was clearly suggesting a preference for ecommerce, with marketplaces such as Amazon leading the way due to greater convenience and price advantages.
Businesses that recognised and understood the trend could better prepare for the digital shopping season, placing greater emphasis on their online marketing tactics to encourage purchases and allocating resources to ensure product availability and on-time delivery.
While on the other hand, businesses who ignored, or simply did not utilise the information available to them, would have been left with overstocked shops and now, out of season items that would have to be heavily discounted or worse, disposed of.
Similarly, search and sales data can be used to understand changing consumer needs, and consequently, what items businesses should be ordering, manufacturing, marketing and selling for the best returns.
For instance, understandably, in 2020, DIY was at its peak, with increases in searches for “DIY facemasks”, “DIY decking” and “DIY garden ideas”. For those who had recognised the trend early on, they had the chance to shift their offerings and marketing in accordance, in turn really reaping the rewards.
So, paying attention to data certainly does pay off. And thanks to smarter and more sophisticated ways of collecting data online, such as cookies, and through AI and machine learning technologies, the value and use of such information is only likely to increase.
The future, therefore, looks bright. But even with all this potential at our fingertips, there are a number of issues businesses may face if their approach relies entirely on a data and insight-driven approach. Just like disregarding its power and potential can be damaging, so can using it as the sole basis upon which important decisions are based.
While the value of data for understanding the market and consumer patterns is undeniable, its value is only as rich as the quality of data being inputted. So, if businesses are collecting and analysing their data on their own activity, and then using this to draw meaningful insight, there should be strong focus on the data gathering phase, with attention given to what needs to be collected, why it should be collected, how it will be collected, and whether in fact this is an accurate representation of what it is you are trying to monitor or measure.
Human error can become an issue when this is done by individuals or teams who do not completely understand the numbers and patterns they are seeing. There is also an obstacle presented when there are various channels and platforms which are generating leads or sales for the business. In this case, any omission can skew results and provide an inaccurate picture. So, when used in decision making, there is the possibility of ineffective and unsuccessful changes.
But while data gathering becomes more and more autonomous, the possibility of human error is lessened. Although, this may add fuel to the next issue.
Drawing a line
The benefits of data and insights are clear, particularly as the tasks of collection and analysis become less of a burden for businesses and their people thanks to automation and AI advancements. But due to how effortless data collection and analysis is becoming, we can only expect more businesses to be doing it, meaning its ability to offer each individual company something unique is also being lessened.
So, businesses need to look elsewhere for their edge. And interestingly, this is where a line should be drawn and human judgement should be used in order to set them apart from the competition and differentiate from what everyone else is doing.
It makes perfect sense when you think about it. Your business is unique for a number of reasons, but mainly because of the brand, its values, reputation and perceptions of the services you are upheld by. And it’s usually these aspects that encourage consumers to choose your business rather than a competitor.
But often, these intangible aspects are much more difficult to measure and monitor through data collection and analysis, especially in the autonomous, number-driven format that many platforms utilise.
Here then, there is a great case for businesses to use their own judgements, expertise and experiences to determine what works well and what does not. For instance, you can begin to determine consumer perceptions towards a change in your product or services, which quantitative data may not be able to pick up until much later when sales figures begin to rise or fall. And while the data will eventually pick it up, it might not necessarily be able to help you decide on what an appropriate alternative solution may be, should the latter occur.
Human judgement, however, can listen to and understand qualitative feedback and consumer sentiments which can often provide much more meaningful insights for businesses to base their decisions on.
So, when it comes to competitor analysis, using insights generated from figure-based data sets and performance metrics is key to ensuring you are doing the same as the competition.
But if you are looking to get ahead, you may want to consider taking a human approach too.
Article | February 18, 2021
According to software vendors executing the big data projects, the answer is clear: More data means more options. Then add a bit of machine learning (ML) for good measure to get told what to do, and the revenue will thrive.This is not really feasible. Therefore, before starting a big data project, a checklist might come in handy.Make sure that the insights gained through machine learning are actionable. Gaining insights is always good, but it is even better if you can act on this new knowledge.A shopping basket analysis shows which products are sold together. What to do with that information?Companies could place the two products in opposite corners of the shop, so customers walk through all areas and will find other products to buy in addition. Or they could place both products next to each other so each boosts the sales of the other. Or how about discounting one product to gain more customers?As all actions have unknown side effects, companies have to decide for themselves which action makes sense to take in their case.
Article | February 18, 2021
2 Top Data Storage Trends That Simplify Data Management
2.1 AI Storage Continues to be The Chief
2.2 Price Markdown in Flash Storage
2.3 Hybrid Multi Cloud for The Win
2.4 Increased Significance of Software-Defined Storage
2.5 Non-Volatile Memory Express (NVMe) Beats Data Center Fabrics
2.6 Acceleration of Storage Class Memory
2.7 Hyperconverged Storage – A Push to Edge Computing
3 The Future of Data Storage
There’s more to data than just to store it. Organizations not only have the responsibility of dealing with a plethora of data, but are also anticipated of safeguarding it. One of the primary alternatives that enterprises are indulging in to keep up with the continuous data expansion is data storage entities and applications.
A recent study conducted by Statista revealed that worldwide spending on data storage units is expected to exceed 78 billion U.S. dollars by 2021. Going by these storage stats, it can be certainly said that data is going to be amplified at a much faster rate, and companies do not have a choice but to be geared up for a data boom and still be relevant.
When it comes to data management/storage, information technology has risen to all its glory with concepts like machine learning. While the idea of such profound approaches is thrilling, the real question boils down to whether organizations are ready as well as equipped enough to handle them. The answer to this might be NO.
But, can companies make changes and still thrive? Most definitely, YES!
To make this concept more understandable, here is a list of changes/trends that companies should adopt to make data storage a lot more easy and secure.
2. Top data storage trends that simplify data management
Data corruption is one big issue that most companies face. The complications that unfold further because of the corruption of data are even more complicated to resolve. To fix this and other such data storage problems, companies have come up with trends that are resilient and flexible. These trends have the capability of making history in the world of technology, so, you better gear up to learn and later adapt to them.
2.1 AI storage continues to be the chief
The speed with which AI hit the IT world just doesn’t seem to slow down even after all these years. We say this because, amongst all other concepts that were and are constantly being introduced, artificial intelligence is one applied science that has made the most amount of innovations. To further add to this, AI is now making enterprise data storage process easier with its various subsets like machine learning and deep learning. This technology is helping companies in accumulating multiple layers of data in a more assorted format. It is automating IT storages including data migrating, archiving, protecting, etc. With AI, companies will be able to control data storage across multiple locations and storage platforms.
2.2 Price markdown in Flash storage
As per a report by Markets and Markets, the overall All-Flash Array Market was valued at USD 5.9 billion in 2018 and is expected to reach USD 17.8 billion by 2023, at a CAGR of 24.53% during this period. This growth only states that the need for all-flash storage is only going to broaden. Flash storage has always been a choice that most companies stayed away from mainly because of the price. But with this new trend of adopting flexible data storage ways coming in, flash storage has been offered at a much-depreciated price. The drop in the cost of this storage technology will finally enable businesses of all sizes to invest in this high-performance solution.
READ MORE: HOW BUSINESS ANALYTICS ACCELERATES YOUR BUSINESS GROWTH
2.3 Hybrid multi cloud for the win
With data growing every minute, just a “cloud” strategy will not be enough. In this wave of data storage services, hybrid multi-cloud is one concept that is helping manage off-premises data. With this growing concept, IT authorities will be able to collect, segregate and store, on-premises, and off-premises data in a much-sophisticated manner. This will enable in centrally managing while reducing the effort of data storage by automating policy-based data placement across a hybrid of multi-cloud and storage types.
2.4 Increased significance of software-defined storage
More the data, less reliability on hardware devices – this is the growing attitude of most companies. This fear certainly has the possibility of becoming a reality. Hence, an addition to the cybersecurity strategy that companies can make is adopting software-defined storage. This approach of data storage disconnects the underlying physical storage hardware. It is programmed in a way that can function on policy-based management of resources, automated provision, and computerized storage capacity reassignment. Due to the automated function, scaling up and down of data is also faster. Some of the biggest advantages of this trend will be the governance, data protection, and security it will provide to the entire loop.
2.5 Non-Volatile Memory Express (NVMe) beats data center fabrics
NVMe – as ornate as the name sounds, is a concept that is freshly introduced with the aim of making data storage simpler. Non-Volatile Memory Express is a concept that enables accessibility of high-speed storage media. It is a protocol that is showing great results in a short amount of time of its inception. NVMe not only increases the performance value of existing applications, but also enables new applications to real-time workload processing. This feature of high performance and low latency is surely a highlight of the concept. All in all, this entire trend seems to have a lot of potential that are yet to be explored.
READ MORE: HOW TO MAXIMIZE VALUE FROM DATA COLLECTED FOR BUSINESSES SUCCESS
2.6 Acceleration of storage class memory
Storage class memory is a perfect combination of flash storage and NVMe. This is because it perfectly fills in the gap between server storage and external storage. As data protection is one of the major concerns of enterprises, this upcoming trend, does not only protect data but also continually stores and improves it for easier segregation. A clear advantage that storage class memory has over flash and NVMe storages is that it provides memory-like byte-addressable access to data thus reducing piling up of irrelevant data. Another benefit of this trend is that it indulges in deeper integration of data for ensuring high performance and top-level data security.
2.7 Hyperconverged storage – a push to edge computing
The increased demand for hyper converged storage is a result of the growth of hybrid cloud and software-defined infrastructure. Besides these technologies, its suitability for retail settings and remote offices is add on to its already existing set of features. It’s the capability of capturing data from a distance also enables cost-effectiveness and scales down the need to store everything on a public cloud. Hyper converged storage if used in its true essence can simplify IT operations and data storage for enterprises of all sizes.
3. The future of data storage
According to the Internet World Stats, more than 4.5 billion internet users around the world relentlessly create an astronomical amount of data. This translates to propel companies into discovering methods or applications that help them store this data safe from harmful ransomware attacks and still use it productively for their advantage. One of the prime changes that can be estimated about the future of data storage is that companies will have to adapt to the rapid changes, and mould their process to enable quick and seamless storage of data. Another enhancement would be that IT managers and responsible authorities would have to be updated and proactive at all times to know what data storage has been newly introduced, and how it can be used for the company’s advantage.
Here’s a thing, amongst all the research that enterprises are conducting, not all data storage technologies will end up becoming a hit, and will fulfil the specification of high-speed storage. But, looking at all the efforts that researchers are taking, we don’t think they are going to stop any sooner and neither is the augmentation of data!
Article | February 18, 2021
What are your physical assets telling you? Are they performing to design capacity? Are they providing the expected return on investment? Are they aging and in need of capital investment or replacement?
We live in an increasingly data-rich environment, and successful companies must take full advantage of transforming data to information. Among manufacturers there’s growing awareness of how data and analytics can drive operations and maintenance, predicting breakdowns and reducing downtime. However, it’s possible to go further. A mostly untapped opportunity for manufacturers exists in the use of operational data from the factory floor to inform better capital allocation decisions.