We create a professional-looking website for you very easy quickly, your small business needs to be in the online space. Research from the E-commerce Wiki indicates that 88% of consumers now research purchases online before purchasing in a store.
We create a simple website that describes who you are, what you do, and how to contact you will suffice for many small businesses. Contact us, we assist to build your website with the minimum, your site should contain:
Your business name
A summary of what you do—your products and services
Your contact information
Your address, including a Google Maps link
Your mission, e.g. “We make the best pizza in town…”
Testimonials from customers
Depending on your target market, social media can be a great way to promote your business as well. Establishing a presence on Facebook, Twitter, and Instagram is standard for most businesses these days. We have the expertise to support and implement your social media requirements and integration.
If you do nothing else with mobile technology, we will help you to make sure that your online presence, including your business website, is mobile friendly. Increasing numbers of people are surfing and searching with their phones—even when they’re at home.
But there are two other trends that could benefit your small business from our expertise. The first is mobile marketing. There are myriad mobile-specific strategies you could be using to reach your target market with great effect, from text message advertising and mobile display ads to having your own business app designed.
Mobile payment systems represent your other opportunity. The choices for paying by phone are now endless. Offering pay-by-phone services is a significant convenience to customers, but your small business could also realize considerable savings and profits from being able to use our services.
We help you to get into the Cloud
There is no doubt that cloud computing has levelled the playing field for startup businesses, but the serious advantages of using the cloud for “ordinary” established businesses are not always discussed.
Cost savings and access from anywhere are the biggest advantages to moving some of your business processes to the cloud. If, for instance, your business changes from a desktop small-business accounting program to a cloud-based accounting application, you would no longer have to install desktop software (saving IT costs for installation, backups, updates, etc.) and you can access your business accounts from anywhere, including from mobile devices.
Make This Year Your Best Ever
Here’s the big takeaway: Success is not a given. Given the global challenges and if you want your small business to be more successful this year, we can assist you to make the necessary changes to bring that about.
That work may be as simple as investing in our products and services as challenging as changing your thinking about some of your business processes. But you haven’t brought your business this far only to let it stagnate, have you? Make the next year your best year yet. Visit our website www.bluedart.co.za or contact +27 809 0317 to find out more.
Technology is now evolving at such a rapid pace that annual predictions of trends can seem out-of-date before they even go live as a published blog post or article. As technology evolves, it enables even faster change and progress, causing an acceleration of the rate of change, until eventually, it will become exponential.
Technology-based careers don’t change at the same speed, but they do evolve, and the savvy IT professional recognizes that his or her role will not stay the same. And an IT worker of the 21st century will constantly be learning (out of necessity if not desire).
What does this mean for you? It means staying current with technology trends. And it means keeping your eyes on the future, to know which skills you’ll need to know and what types of jobs you want to be qualified to do. Here are eight technology trends you should watch for in 2020, and some of the jobs that will be created by these trends.
1. Artificial Intelligence (AI)
Artificial Intelligence, or AI, has already received a lot of buzz in recent years, but it continues to be a trend to watch because its effects on how we live, work, and play are only in the early stages. In addition, other branches of AI have developed, including Machine Learning, which we will go into below. AI refers to computer systems built to mimic human intelligence and perform tasks such as recognition of images, speech or patterns, and decision making. AI can do these tasks faster and more accurately than humans.
Five out of six Americans use AI services in one form or another every day, including navigation apps, streaming services, smartphone personal assistants, ride-sharing apps, home personal assistants, and smart home devices. In addition to consumer use, AI is used to schedule trains, assess business risk, predict maintenance, and improve energy efficiency, among many other money-saving tasks.
AI is one part of what we refer to broadly as automation, and automation is a hot topic because of potential job loss. Experts say automation will eliminate 73 million more jobs by 2030. However, automation is creating jobs as well as eliminating them, especially in the field of AI: Pundits predict that jobs in AI will number 23 million by 2020. Jobs will be created in development, programming, testing, support, and maintenance, to name a few. Artificial Intelligence architect is one such job. Some say it will soon rival data scientists in need of skilled professionals. To learn more about potential jobs in AI, read about building a career in AI, or why you should earn an AI certification.Offer Expires In
Machine Learning is a subset of AI. With Machine Learning, computers are programmed to learn to do something they are not programmed to do: they learn by discovering patterns and insights from data. In general, we have two types of learning, supervised and unsupervised.
While Machine Learning is a subset of AI, we also have subsets within the domain of Machine Learning, including neural networks, natural language processing (NLP), and deep learning. Each of these subsets offers an opportunity for specializing in a career field that will only grow.
Machine Learning is rapidly being deployed in all kinds of industries, creating a huge demand for skilled professionals. The Machine Learning market is expected to grow to $8.81 billion by 2022. Machine Learning applications are used for data analytics, data mining, and pattern recognition. On the consumer end, Machine Learning powers web search results, real-time ads, and network intrusion detection, to name only a few of the many tasks it can do.
In addition to completing countless tasks on our behalf, it is generating jobs. Machine Learning jobs rank among the top emerging jobs on LinkedIn, with almost 2,000 job listings posted. And these jobs pay well: In 2017, the median salary for a machine learning engineer was $106,225. Machine Learning jobs include engineers, developers, researchers, and data scientists.
3. Robotic Process Automation or RPA
Like AI and Machine Learning, Robotic Process Automation, or RPA, is another technology that is automating jobs. RPA is the use of software to automate business processes such as interpreting applications, processing transactions, dealing with data, and even replying to emails. RPA automates repetitive tasks that people used to do. These are not just the menial tasks of a low-paid worker: up to 45 percent of the activities we do can be automated, including the work of financial managers, doctors, and CEOs.
For you as an IT professional looking to the future and trying to understand technology trends, RPA offers plenty of career opportunities, including developer, project manager, business analyst, solution architect, and consultant. And these jobs pay well. SimplyHired.com says the average RPA salary is $73,861, but that is the average compiled from salaries for junior-level developers up to senior solution architects, with the top 10 percent earning over $141,000 annually. So, if you’re keen on learning and pursuing a career in RPA, the Introduction to Robotic Process Automation (RPA) course should be the next step you take to kickstart an RPA career.
4. Edge Computing
Formerly a technology trend to watch, cloud computing has become mainstream, with major players AWS (Amazon Web Services), Microsoft Azure and Google Cloud dominating the market. The adoption of cloud computing is still growing, as more and more businesses migrate to a cloud solution. But it’s no longer the emerging technology.
As the quantity of data we’re dealing with continues to increase, we’ve realized the shortcomings of cloud computing in some situations. Edge computing is designed to help solve some of those problems as a way to bypass the latency caused by cloud computing and getting data to a data center for processing. It can exist “on the edge,” if you will, closer to where computing needs to happen. For this reason, edge computing can be used to process time-sensitive data in remote locations with limited or no connectivity to a centralized location. In those situations, edge computing can act like mini datacenters. Edge computing will increase as the use of the Internet of Things (IoT) devices increases. By 2022, the global edge computing market is expected to reach $6.72 billion. As with any growing market, this will create various jobs, primarily for software engineers.
If you wish to get a thorough understanding of edges means, and how is it different from cloud computing, give it a read here!Offer Expires In
Virtual Reality (VR) immerses the user in an environment while Augment Reality (AR) enhances their environment. Although VR has primarily been used for gaming thus far, it has also been used for training, as with VirtualShip, a simulation software used to train U.S. Navy, Army, and Coast Guard ship captains. The popular Pokemon Go is an example of AR.
Both VR and AR have enormous potential in training, entertainment, education, marketing, and even rehabilitation after an injury. Either could be used to train doctors to do surgery, offer museum-goers a deeper experience, enhance theme parks, or even enhance marketing, as with this Pepsi Max bus shelter.
There are major players in the VR market, like Google, Samsung, and Oculus, but plenty of startups are forming and they will be hiring, and the demand for professionals with VR and AR skills will only increase. Getting started in VR doesn’t require a lot of specialized knowledge. Basic programming skills and a forward-thinking mindset can land a job, although other employers will be looking for optics as a skill-set and hardware engineers as well.
Cybersecurity might not seem like emerging technology, given that it has been around for a while, but it is evolving just as other technologies are. That’s in part because threats are constantly new. The malevolent hackers who are trying to illegally access data are not going to give up any time soon, and they will continue to find ways to get through even the toughest security measures. It’s also in part because new technology is being adapted to enhance security. As long as we have hackers, we will have cyber security as an emerging technology because it will constantly evolve to defend against those hackers.
Although most people think of blockchain technology in relation to cryptocurrencies such as Bitcoin, blockchain offers security that is useful in many other ways. In the simplest of terms, blockchain can be described as data you can only add to, not take away from or change. Hence the term “chain” because you’re making a chain of data. Not being able to change the previous blocks is what makes it so secure. In addition, blockchains are consensus-driven, so no one entity can take control of the data. With blockchain, you don’t need a trusted third-party to oversee or validate transactions. You can refer to our Blockchain tutorial for a detailed and thorough understanding of the technology.
Several industries are involving and implementing blockchain, and as the use of blockchain technology increases, so too does the demand for skilled professionals. In that regard, we are already behind. According to Techcrunch.com, blockchain-related jobs are the second-fastest growing category of jobs, with 14 job openings for every one blockchain developer. A blockchain developer specializes in developing and implementing architecture and solutions using blockchain technology. The average yearly salary of a blockchain developer is $130,000. If you are intrigued by Blockchain and its applications and want to make your career in this fast-growing industry, then this is the right time to learn Blockchain and gear up for an exciting future.
8. Internet of Things (IoT)
Many “things” are now being built with WiFi connectivity, meaning they can be connected to the Internet—and to each other. Hence, the Internet of Things, or IoT. The Internet of Things is the future and has already enabled devices, home appliances, cars, and much more to be connected to and exchange data over the Internet. And we’re only in the beginning stages of IoT: the number of IoT devices reached 8.4 billion in 2017 is expected to reach 30 billion devices by 2020.
As consumers, we’re already using and benefitting from IoT. We can lock our doors remotely if we forget to when we leave for work and preheat our ovens on our way home from work, all while tracking our fitness on our Fitbits and hailing a ride with Lyft. But businesses also have much to gain now and in the near future. The IoT can enable better safety, efficiency, and decision making for businesses as data is collected and analyzed. It can enable predictive maintenance, speed up medical care, improve customer service, and offer benefits we haven’t even imagined yet.
However, despite this boon in the development and adoption of IoT, experts say not enough IT professionals are getting trained for IoT jobs. An article at ITProToday says we’ll need 200,000 more IT workers that aren’t yet in the pipeline, and that a survey of engineers found 25.7 percent believe inadequate skill levels to be the industry’s biggest obstacle to growth. For someone interested in a career in IoT, that means easy entry into the field if you’re motivated, with a range of options for getting started. Skills needed include IoT security, cloud computing knowledge, data analytics, automation, understanding of embedded systems, device knowledge, to name only a few. After all, it’s the Internet of Things, and those things are many and varied, meaning the skills needed are as well.
So, What’s Next?
Although technologies are emerging and evolving all around us, these eight technologies offer promising career potential now and for the foreseeable future. And all eight are suffering from a shortage of skilled workers, meaning the time is right for you to choose one, get trained, and get on board at the early stages of the technology, positioning you for success now and in the future.
Check out the Simplilearn’s video on “Top Technologies to Learn in 2020”.
The most recent jobs report, showing a high unemployment rate in 2018, also portrays the global economy capable of generating plenty of work. But what if, in the not-too-distant future, there won’t be enough jobs to go around?
That’s what some economists believe will happen as robots and artificial intelligence increasingly becomes capable of performing human tasks. Researchers, for example, estimate that nearly half of all jobs may be at risk in the coming decades, with lower-paid occupations among the most vulnerable.
Wondering how vulnerable your job might be? Refer to the chart below to see what the researchers think is the probability of your job being automated.
Deep-learning model has been used successfully on patients, may lead to more consistent screening procedures.
Researchers from MIT and Massachusetts General Hospital have developed an automated model that assesses dense breast tissue in mammograms — which is an independent risk factor for breast cancer — as reliably as expert radiologists.
This marks the first time a deep-learning model of its kind has successfully been used in a clinic on real patients, according to the researchers. With broad implementation, the researchers hope the model can help bring greater reliability to breast density assessments across the nation.
It’s estimated that more than 40 percent of U.S. women have dense breast tissue, which alone increases the risk of breast cancer. Moreover, dense tissue can mask cancers on the mammogram, making screening more difficult. As a result, 30 U.S. states mandate that women must be notified if their mammograms indicate they have dense breasts.
But breast density assessments rely on subjective human assessment. Due to many factors, results vary — sometimes dramatically — across radiologists. The MIT and MGH researchers trained a deep-learning model on tens of thousands of high-quality digital mammograms to learn to distinguish different types of breast tissue, from fatty to extremely dense, based on expert assessments. Given a new mammogram, the model can then identify a density measurement that closely aligns with expert opinion.
“Breast density is an independent risk factor that drives how we communicate with women about their cancer risk. Our motivation was to create an accurate and consistent tool, that can be shared and used across health care systems,” says Adam Yala, a PhD student in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and second author on a paper describing the model that was published today in Radiology.
The other co-authors are first author Constance Lehman, professor of radiology at Harvard Medical School and the director of breast imaging at the MGH; and senior author Regina Barzilay, the Delta Electronics Professor at CSAIL and the Department of Electrical Engineering and Computer Science at MIT and a member of the Koch Institute for Integrative Cancer Research at MIT.
The model is built on a convolutional neural network (CNN), which is also used for computer vision tasks. The researchers trained and tested their model on a dataset of more than 58,000 randomly selected mammograms from more than 39,000 women screened between 2009 and 2011. For training, they used around 41,000 mammograms and, for testing, about 8,600 mammograms.
Each mammogram in the dataset has a standard Breast Imaging Reporting and Data System (BI-RADS) breast density rating in four categories: fatty, scattered (scattered density), heterogeneous (mostly dense), and dense. In both training and testing mammograms, about 40 percent were assessed as heterogeneous and dense.
During the training process, the model is given random mammograms to analyze. It learns to map the mammogram with expert radiologist density ratings. Dense breasts, for instance, contain glandular and fibrous connective tissue, which appear as compact networks of thick white lines and solid white patches. Fatty tissue networks appear much thinner, with gray area throughout. In testing, the model observes new mammograms and predicts the most likely density category.
The model was implemented at the breast imaging division at MGH. In a traditional workflow, when a mammogram is taken, it’s sent to a workstation for a radiologist to assess. The researchers’ model is installed in a separate machine that intercepts the scans before it reaches the radiologist, and assigns each mammogram a density rating. When radiologists pull up a scan at their workstations, they’ll see the model’s assigned rating, which they then accept or reject.
“It takes less than a second per image … [and it can be] easily and cheaply scaled throughout hospitals.” Yala says.
On over 10,000 mammograms at MGH from January to May of this year, the model achieved 94 percent agreement among the hospital’s radiologists in a binary test — determining whether breasts were either heterogeneous and dense, or fatty and scattered. Across all four BI-RADS categories, it matched radiologists’ assessments at 90 percent. “MGH is a top breast imaging center with high inter-radiologist agreement, and this high quality dataset enabled us to develop a strong model,” Yala says.
In general testing using the original dataset, the model matched the original human expert interpretations at 77 percent across four BI-RADS categories and, in binary tests, matched the interpretations at 87 percent.
In comparison with traditional prediction models, the researchers used a metric called a kappa score, where 1 indicates that predictions agree every time, and anything lower indicates fewer instances of agreements. Kappa scores for commercially available automatic density-assessment models score a maximum of about 0.6. In the clinical application, the researchers’ model scored 0.85 kappa score and, in testing, scored a 0.67. This means the model makes better predictions than traditional models.
In an additional experiment, the researchers tested the model’s agreement with consensus from five MGH radiologists from 500 random test mammograms. The radiologists assigned breast density to the mammograms without knowledge of the original assessment, or their peers’ or the model’s assessments. In this experiment, the model achieved a kappa score of 0.78 with the radiologist consensus.
Next, the researchers aim to scale the model into other hospitals. “Building on this translational experience, we will explore how to transition machine-learning algorithms developed at MIT into clinic benefiting millions of patients,” Barzilay says.
Vahé Torossian – Corporate Vice President, Microsoft Corporation & President Microsoft Western Europe
I truly believe that Artificial Intelligence (AI) carries enormous potential to make the world a better place and drive transformational change in some of the most important aspects of our lives – how we live, play, interact with each other and, last but not least, work. AI is also full of surprises. When it comes to AI in the workplace, we’ve noticed that a key and common trait of companies that use AI successfully is actually — Emotional Intelligence (EQ).
Simply defined, EQ is the ability to identify and understand emotions. In a professional context, it means having the ability to handle relationships with empathy, understand what motivates people, and creating an open and collaborative environment (with technology or other tools) that empowers people to do their best work. Throughout my career, I’ve seen first-hand how EQ can take an organization to a whole new level.
We recently learned a lot about AI, and its fascinating relation with EQ, from a new study commissioned by Microsoft and conducted by Ernst & Young. Released publicly today, Artificial Intelligence in Europe seeks to help us understand the AI strategies of 277 major companies across seven business sectors and 15 countries in Europe. It examines how ready these companies are to adopt AI, how the organizations rate the impact and benefits from AI implementations, and what they perceive as the keys to success.
The research found a strong and clear correlation between the maturity of AI deployments by European companies and how those organizations rate themselves on EQ. A solid majority—80 percent—of the companies most advanced in AI considered themselves to be “strongly emotionally intelligent”. On the flip side, only 16 percent of the companies considered least mature in AI rated themselves as more than moderately competent in EQ.
The correlation between EQ and AI is not obvious. Researchers asked companies about eight organizational capabilities considered necessary to successfully harness AI. EQ was rated as the least important. Companies that are less mature in their use of AI are often focused on more immediate needs such as data management and advanced analytics, which organizations ranked as the most important capabilities considered by the study.
This makes a lot of sense to me. At Microsoft we believe the promise of AI lies in what it can do to amplify our ingenuity – the power of human PLUS machine. It may well be that you must have an emotionally intelligent business culture, open to change and to new ways of working, to successfully use AI. Think about it… since AI is relatively new for most organizations, solving business and customer challenges with AI often requires that systems be designed and built from the ground up. Doing that requires business acumen, technological savvy, and a willingness to embrace the unknown. Another interesting finding in the research was that 57 percent of the companies interviewed expect that AI will have a high impact on business areas that are entirely unknown to the company today. Business leaders who are ready to embrace and tackle the unknown are already demonstrating the kind of openness that is fundamental to EQ.
I believe that businesses can open the door for tremendous growth opportunities by fostering a culture that is emotionally intelligent and that empowers workers with AI tools. 61 percent of the 277 companies included in the research expect AI to free up employees to do what people do best: think creatively and figure out how to use technological tools to drive business success, optimize operations, and engage customers in new and exciting ways. It’s hard to imagine a business leader that doesn’t want that sort of outcome. One of our challenges is that, in Europe, we have a long way to go to get there; just four percent of respondents said that AI is contributing to company-wide processes today. So all I see is opportunity!
Technology for technology’s sake has never been the answer. We must be aligned on the ultimate impact technology can have and be working toward clear and common goals – for the benefit of our customers and our society. To impact real change and to harvest the huge potential of AI, leaders must establish that clarity and create an open and collaborative culture that supports people with intelligent technology, so they can bring their very best to work every day. Then we will truly see the power of AI, to create a better tomorrow.
Effective IT governance is a critical tool for CIOs to align their organizations and efforts to support business strategy and create shareholder value. Given the rapidly changing and evolving technology options that confront CIOs and business leaders, making sure the right decisions are being made about investments in IT is an essential priority.
There are many misconceptions about what constitutes a comprehensive IT governance model and how it is implemented. IT governance is more than just:
Having a steering committee that meets periodically to review and approve IT plans and budgets
Involving the business on an annual basis to assist in assigning IT priorities
Using financial metrics such as ROI to determine whether to invest in specific initiatives
Instituting best practices to ensure projects are completed on time and within budget
Measuring and reporting on user satisfaction of IT services
While all of the above are important yardsticks to assess the impact of IT, taken one by one they do not guarantee that IT is contributing to the type of business performance that provides a competitive advantage and achieves enterprise business goals. Most of all, they do not constitute an effective IT governance program.
How Best to Think About IT Governance
IT governance comprises a decision framework and set of processes that allow CIOs and management to articulate desired outcomes through programs that enable the organization to attain these results. The decision framework and the corresponding tools and processes to support them must be clearly communicated so that day-to-day activities and decisions are made within this context. In other words, IT governance needs to instil behaviour and awareness that is understood at all levels in the organization, not just by senior management.
Clearly, the desired outcomes that shape IT will vary between industries and organizations. For example, some enterprises may focus on product innovation and accelerated go-to-market strategies while others may strive to create operational efficiencies throughout the value chain. CIOs may also encourage management to consider new technologies such as a big data, real-time analytics initiative or social-media-based customer satisfaction programs to support business performance.
The essential success factor, regardless of the specific initiative undertaken, is the linkage to tangible, measurable top-line or bottom-line business outcomes. As tempting as the latest technology or trend might be, organizations must always calibrate their IT endeavours against this metric to ensure they are not investing financial and human capital where it will yield minimal return and offer no strategic value.
CIOs must take the lead in helping place the organization’s competitive model within the governance-making framework so that the right decisions are being made and, ultimately, institutionalized across the enterprise. From a top-down perspective this means:
Linking business strategy to the IT programs that will be undertaken and funded; this will be reflected and communicated within the IT planning process.
Aligning IT spend and investments to ensure that they reflect the appropriate strategic initiatives. This is a continual process and not just part of the annual budgeting cycle.
Staffing the IT organization with the necessary skills and resources to effectively execute the committed programs.
Implementing effective risk management processes that ensure regulatory compliance, accountability, transparency and resiliency.
Creating a financial scorecard that tracks approved IT investments to each desired outcome measured in delivered business benefits.
Institutionalizing IT Governance
The missing link between a well-thought-out plan endorsed by management and actualization is often the absence of tactical processes and policies both inside and outside of IT. Some critical and foundational disciplines include:
The emergence of enterprise architectures – solutions that support end-to-end business processes – require CIOs to advocate for far greater business involvement than was traditionally required for “siloed” applications. Prerequisites are (1) business sponsorship at an executive level to provide the sense of urgency and commitment of mindshare and resources required and (2) business process owners who oversee and control the impact of new technology throughout the organization. Without these two ingredients, any strategic project will be viewed as IT-centric with little accountability from the business and, by extension, limited commitment to the desired outcomes.
Consistent practices in managing IT projects and delivering solutions within agreed-upon parameters is a basic building block for most organizations. However, within the broader context of an IT governance framework, program management must incorporate metrics that were used within the governance framework. This would include not only the investment analysis but also the desired outcomes that drove the decision-making process. These metrics can be incorporated within dashboards that will help management view progress, benefits and the effectiveness of their decisions. As all effective management practices, IT governance needs to be continually reviewed, assessed and refined with proper measurement and transparency. Program management is essential to bridging decisions to the execution of strategic plans.
By their very nature, IT architectures consist of numerous technical layers and components, making them difficult to relate to in terms of business activities and decision making. Portfolios are useful tools for CIOs to integrate views of IT services and solutions to senior management so that they can be associated with desired outcomes. Often this will result in moving toward architecture standardization as an added dividend that will yield long-term benefits. The move to integrated solutions across the enterprise will require a restructuring of the portfolio as an overall strategy that will reduce IT costs and deliver greater operational efficiencies. The portfolio dimension is another key criteria that must be incorporated within management scorecards to guide future technology investments.
How Best to Move Forward
Developing a comprehensive IT governance program can be a daunting task even for organizations with mature management practices. The best place to start is to become familiar with the COBIT 5 framework and principles. ISACA (Information Systems Audit and Control Association) offers many valuable tools and information that will help with education and putting into place a roadmap for the IT governance journey.
Additionally, consider utilizing an experienced practitioner that can help implement practical and proven strategies to formulate an IT governance program and roadmap. They can also assist in engaging senior management in adopting the necessary practices that will lead to acceptance across the broader organization.
It cannot be stressed enough that IT governance is an ongoing journey that will continually evolve, not a one-time destination. It is up to CIOs to lead the way by helping their organizations think about, evaluate and adopt the “right” IT strategies for their businesses.
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