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Tech

The LASTING Software Big Data experience spans from pharmaceutical industry projects, to the business software and consultancy collaborations we are part of. Digital data is our field of action.

While auditing companies and being part of the preliminary consultancy stage, one can notice in time how the needs and requirements of each partner vary, even if the ultimate goals bring us all together. Staying ahead of the competition, getting a firm grasp on the industrial revolution phenomenon and keeping or making their organizations successful are all common traits for companies, even for industries.

Reaching these goals allows for a wide range of software solutions to come into play. The best solution for you is the one that provides the most suitable, actionable answer to your current needs. Being scalable is a big extra, because what you invest in now will also deliver tomorrow, the next year or in 5 years. Provided you specify this in the consultancy & design phase, a sustainable software solution should always be an integrated scope.

On this line, we ran into an article that deconstructs the Big Data needs – and we want to share a few ideas out of it with you.

 

 

Operational data, a preliminary step to Big Data

While Big Data involves a great deal of external data purchasing, operational data is internal. The ReadWrite article that caught our attention underlines the importance of harnessing this type of data, before making the leap for Big Data.

Mining data for actionable information requires attentive management, accurate analysis, and continuous adjustment, and buying software and raw data doesn’t provide companies with the skills necessary to master these processes overnight”.

In other words, the companies that are new to this need guidance. So do those that have reached the conclusion that something needs to change for the better in the way they do things.

This, as well as trying your hand at the data game by processing operational data, could both use the right partnerships.

The consultants in this field put their know-how and experience at your disposal. Once you successfully deploy operational data solutions, it may be time for big data, or not. Often the optimal solution combines both of the types of data. It all depends on the specifics of your activity.

 

The smaller-scale solutions for digital data, between creativity and customization

Let’s say your organization has a certain operational need. The answer takes the shape of a potential project. Creativity points out a certain type of solution, perhaps even a completely innovative one. When further going into the matter, some aspects become limited by technical elements. You customize down, so to say. What you imagined at a first glance can change. It happens, once confronted with budgeting, resources, compatibility, and project duration or other reasonable expectations.

When done in-house, this stage can be too harsh, or in some cases, not harsh enough. Both are dangerous, because instead of getting things done the right way, you would either settle for a more limited solution, or delay the problem solving by chasing a less realistic projection. By partnering with a software solutions company, you can test these “could be”-s against a backdrop of hands-on experience, industry know how and updated knowledge in the software solutions field.

The second stage of customization can take place when already having a certain skilled software partner. Your operational need can prove one that is familiar across your industry or field. Then the answer to it need not start from scratch. Building upon an already validated solution involves customizing up and the team creates and/or activates new features. Cost-saving and faster, this way of getting a personalized solution is perhaps the most frequent nowadays.

Contact LASTING Software, let’s talk about this and see where it takes us! We are here for your projects!

 

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Tech

5G links to Smart Manufacturing, which links to Industry 4.0. In fact the last two may be seen as one and the same thing.


Smart manufacturing and the Smart Factory is a broad category of manufacturing with the goal of optimizing the manufacturing process. Smart manufacturing is the process that employs computer controls, modeling, big data and other automation to improve manufacturing efficiencies.

Source


Although some big players are still reticent, important 5G promoters continue to develop this technology. Moreover, hands-on demos illustrate its key qualities. Continuous process monitoring is one of the areas 5G should bring shorter lead-times, while returning higher yield.

We took a look at one article occasioned by this year’s Industrial Manufacturing Show held in Chicago:


Industry 4.0 will rely on increasingly fast, secure, and often wireless, data transfers to optimize operations, increase automation and mitigate risk in manufacturing environments.

 

Potential 5G early adopters


Various sensitive industries that would highly benefit from a reduction in the production errors are potential early adopters.


The 5G article mentions the aeronautical industry and the manufacturing industry – when focusing on the production of sophisticate components.


The scope here is to make the collecting and processing of the sensor data, as well as the action of cutting control, take place in under one millisecond.


Research has pointed out that for this type of demands, “5G and cellular wireless can deliver, with its ultra-low latency and high reliability”.

 

What does 5G mean for industrial production?


As mentioned above, no network solutions before 5G have been able to provide instant monitoring and adjustment during production.


An extra benefit is that by storing production and sensor data for each manufactured product, the 5G supported manufacturing enables real-time digital twins. Whenever needed, this data is available and ready to serve in research, analysis, and risk assessment, or to answer other possible demands.

 

While waiting for 5G future developments


As our colleague Ionel Petrut, Project Manager at Lasting Software, mentioned in his presentation held this year for the SACI conference (IEEE 12th International Symposium on Applied Computational Intelligence and Informatics, SACI 2018, Timisoara, Romania):

 

The Internet of Things had a very big impact on the technology as we know today. One important aspect, not yet standardized, is the way in which objects connect to the network to function together. In particular, in the medical field, the Internet of Things faces a high number of technical limitations, most of them related to the electromagnetic emissions.

Until the 5G network will create the infrastructure for sensors to directly connect to the Internet, the connection through Bluetooth Low Energy remains the most suitable solution for Internet of Things connectivity.

 

We prove our software engineering skills and professional commitment by mastering the current technologies involved in the projects we are part of. But we also keep an eye on the latest developments, dreaming of the bold new world of fully deployed IoT capabilities.

 

Contact us for consultancy and partnerships – the future awaits!

 

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Leadership

ZDNet takes a look at the AI and Machine Learning predictions, in what the business environment is concerned. Expected to surge in 2019, the rapid adoption of these new technologies also brings different business challenges.

The article mentions the necessary (and huge) shift that is absolutely required for organizations to thrive. Going from buying “black boxes that will fix our problems and offer us solutions” – as the publication puts it, to the next stage, won’t be easy.

A passive attitude welcomes possible cases of “algorithm sprawl, project management issues, and vendor hype”.

But what modern, wise organizations do? How can we all avoid the so-called bad implementations of AI & ML?

 

 

Who will have to handle AI data?

Since data science is not a magic  trick – although sometimes it may seem so – in order for it to work, key people in your company come in. Apparently, “everyone from mid-level managers to C-level execs are going to use this AI”. They also need to understand how to use it, to be prepared and aware of this new age of technology.

Therefore, determining who will work with your AI data is absolutely necessary. You need the big picture before going into details. However, getting the right big picture requires experience.

Use experts – get consultancy as an ally in this big battle. You want to understand what will be going on, and someone who can put the process into perspective can make you go a long way. Having worked with systems, apps, connected data, Artificial Intelligence and data science, professional consultants can provide a reliable blueprint. How will it work for my business? The answer to this is much more accurate when you obtain it with the right guidance and assistance.

 

What does your AI data need to provide answers for?

As the article we’ve mentioned lists, operating Big Data generates effects that go beyond the lucrative insights.

You will also need to have a strategy and to deliver reports to your board.

As the process evolves at a global level, you will need to choose the most suited AI services pack – from the big tech cloud providers.

Data scientists are still scarce, and the models you will be dealing with lack transparency.

The AI-trained professionals are also scarce, and this specialization just made its way into the academic curriculum. For now, hands-on experience prevails.

Your AI data needs to provide answers and guidelines for all of the above, and more. You will be working with a tool with huge potential that you barely understand. Nevertheless, you need to move relatively fast while making the best choices. The AI tools unleash their potential on the go. Add an extra layer of software solutions – and you have a new functionality. Get on board with the best cloud provider, and you will be able to deploy your tools next-level style.

 

Prepare for the next step, by getting a partner that understands the new technology

It’s not only AI. As we’ve seen, it’s also Machine Learning, Big Data, algorithms, analytics, IoT, embedded sensor software, various layers that have to integrate with each other.

Working all these out into the strategy of your company, while resetting certain functionalities and expanding others – this won’t be easy.

As all things good and new, as overwhelming as it may seem, it needs to be done. The sooner, the better. Make the first step and choose a reliable software partner, one experienced in business digital transformation. Call, talk, schedule the meetings you need, soon you will have a whole new perspective on the matter.

 

We are here for you – our know-how and experience are both rich, and our eagerness and innovative spirit are the right match for this future of technology.

Contact us and let’s find out more about how a potential partnership may look like, and what it can do for both of us!

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Tech

Wearables rank on top of the currently available (and emerging) digital solutions for preventive healthcare. Studies anticipate that the mass-scale implementation of wearables would change human behavior. All this in ways whose amplitude should match the other big digitally-induced changes that we’ve experienced in the past decade.


Computers would have morphed into a new, progressive sense of the term. One of the sources we’ve browsed introduces the “collective wearable” notion. By carrying wearables around, people will provide mobility. Mobility means an enhanced digital perception for this huge network of sensors.


Of course, these devices need to collect, deliver, and answer to commands based on processed data, a thing that requires software. A new generation of software for miniaturized devices would roam around, in the shape of watches, glasses or even part of our garments.


Preventive healthcare, giving wearables a noble use



Which one of us can say he or she doesn’t care to find out details about their health? When it comes to self-centered preoccupations, the adults of today are more responsive than those of past days. We may even compete with kids in our eagerness to connect our wellbeing with the digital environment. Who could resist a visually attractive, efficient and well-promoted device? Especially when it provides precious insights about our body. We would have metrics about the way we sleep, breathe, and exercise, about various physical systems and functions.


Of course, these devices would also link the people who wear them with their physicians. Remember a couple of years ago a nanotechnology that reported whether a patient took the prescribed pills or not? Similarly, doctors could monitor the persons in their care . Remotely. The software layer of this wonderfully connected system would deliver a continuous or periodic stream of data. The wearer would link straight into the dedicated software, into the medical network itself. Notifications and/or warnings could prompt the care professionals to intervene when needed.


The actual healthcare potential is huge. So is the preventive healthcare digital market. With a couple of problems out of the way, the manufacturers can expect a boom. For once, the measurements need to be accurate. Another major issue already publicized would be the cyber-security one. No one wants to carry around his/her wrist an open invitation to hackers everywhere.


Both risks point out a key element – quality is needed. High-quality embedded software and software engineering in all layers, from the UI to the data processing system.


Perspectives


How to be successful and build/maintain a notable reputation in the healthcare wearables market? All the involved entities need to make sure quality and reliability are their main goals. With the potential audience spanning worldwide, you would want to get it right from the first time.

Software solutions partners that have accumulated experience in digital healthcare so far are a wise way to go.

As you may have noticed in other posts, we have the know-how and experience that your digital healthcare project needs. Contact us for details!

 

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News

ZDNet explores the way AI, the cloud, and Big Data in “the AI regeneration era”. The industry dubbed the adjacent infrastructure stack Industry 3.0. Due to the new generation of AI chips, data-centric software tasks should benefit in terms of both operational databases and analytics, as well as in what machine learning (ML) implies.

The easier way of handling Big Data can make companies of all sizes and from any location access new operational horizons. But organizing Big Data processing still involves a series of key decisions, which often call for experienced consultants. The pharmaceutical companies have a number of hard choices in the cloud and on-premise already laid out for them.

Bear in mind that the LASTING Software implementation of analytical algorithms and engines for statistical analysis is at the base of the world leading, FDA-approved solution. Our solution is being used by 93% of the world’s pharmaceutical companies. We will therefore walk you through the main expected pharma industry challenges, inspired by the article we mentioned.

 

The importance of processing units in accelerating your software workloads

It’s more exactly about GPUs – Graphical Processing Units, the ones that “leverage parallelism” and better keep up with Moore’s law. Their architecture responded to the new challenges well, and now one of the GPU main producers (NVIDIA), announced a set of innovative products with a new architecture.

Hardware to match the upgraded modern request is therefore on the way. But the software is also of importance. Seeing how “how GPUs are currently the AI chip of choice for ML workloads”, the ML libraries come into play.

For detailed recommendations, you may access the original article. What you need to remember is that “GPUs can greatly accelerate workloads that can be broken down in parts to be executed in parallel”. Enough said.

 

Field Programmable Gateway Arrays and their software scope

FPGAs, simplistically describable as “boards containing low-level chip fundamentals, such as AND and OR gates” are not new. Specific tasks or applications find their correspondence in the hardware description language (HDL) that specifies the FPGAs’ configuration.

Changing the said configuration at need suffers from a certain software layer immaturity. This time, the player that stands out is Intel. By investing into FPGAs R&D, this company tries to catch up on GPUs with a new line of next-gen FPGAs.

Again, the software is crucial. Along with it, the databases and libraries need to support the FPGA-accelerated analytics.  

 

Once having decided what you want, different choices ensue

To quote our inspirational article of the week: “Should you build your own infrastructure, or use the cloud? Should you wait until offerings become more mature, or jump onboard now and reap the early adopter benefits? Should you go for GPUs, or FPGAs? And then, which GPU or FPGA vendor?”

You may check some of the details and possible answers put forth by the author.

If you can make sense of them, or even get the big picture, then you must be familiar with both hardware and software – kudos to you.

Even so, the activity of your company might need the time to focus on different matters. You can still use a partnership where you can state what you need, infrastructure-wise, and your software solutions partner would deliver it.

Unable to follow the detailed options presented by ZDNet? Then the assumption that your company is a typical pharmaceutic industry entity could be the right one. No need to get stuck trying to learn software-specific notions or trying to make sense by yourself what would the best hardware elements be.

 

The multitude of available options pushes for the right partnerships. The wisest, poised for efficiency and success organizations learn to delegate tasks. To make next-gen digitization simple and get right to the point where you benefit from it, find the right software solutions partner.

We are waiting for your email or call!

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