6 Predictions About Data In 2020 And the Coming Decade

January 8th, 2020 by blogadmin No comments »

It’s difficult to make predictions, especially about the future. But one fairly safe prediction is that data will continue eating the world in 2020 and the coming decade. The most important tech trend since the 1990s will no doubt accentuate its presence in our lives, for better or for worse.

At the beginning of the last decade, IDC estimated that 1.2 zettabytes (1.2 trillion gigabytes) of new data were created in 2010, up from 0.8 zettabytes the year before. The amount of the newly created data in 2020 was predicted to grow 44X to reach 35 zettabytes (35 trillion gigabytes). Two years ago, we were already at 33 zettabytes, leading IDC to predict that in 2025, 175 zettabytes (175 trillion gigabytes) of new data will be created around the world.
The most important new tech development of the passing decade has been the practical success of deep learning (popularly known as “artificial intelligence” or “AI”), the sophisticated statistical analysis of lots and lots of data or what I have called Statistics on Steroids (SOS). In the coming decade, data will continue to beget data, to break boundaries, to drive innovation and profits, and create new challenges and concerns.

Faster networks will re-energize the data virtuous cycle

The constant increase in data processing speeds and bandwidth, the nonstop invention of new tools for creating, sharing, and consuming data, and the steady addition of new data creators and consumers around the world, ensure that data growth continues unabated. Data begets more data in a constant virtuous cycle.
But from time to time there is a specific tool or technology that act as a new catalyst. Over the last decade such catalysts were smart phones and social networks. Over the next few years, a new catalyst will be 5G networks, and by 2030, 6G networks with speeds of 1 terabyte per second. Internet delivered via satellites will play a similar role of accelerating the movement of data and reducing latency in the not-distant future.

There will be many new places for data to emerge and spread

Data fills all voids. Even after thirty-five years of enterprise “digital transformation” and twenty-five years since the big data big bang (i.e., the Web, popularly known as “the internet”), there are still a few billion unconnected people and industries that are still primarily analog. The people of Asia and Africa are correcting the former lacuna and sectors such as agriculture, healthcare, and education provide the missing pieces for the latter. Other dominant (and relatively new) sources of data creation and consumption will be things such as sensors that enable new locations for enterprises for collecting and even processing and analyzing data and things that move such as automobiles.
In addition, enterprises will accelerate their shift from focusing on managing (collecting, storing, analyzing) internal data to investing the greater part of their IT resources in managing (collecting, storing, analyzing) external data, most of it “unstructured,” with a significant share of this data emerging from new audio and video sources.

Synthetic data will add a new dimension to data growth

Deep learning is brute force AI. Unlike Deep Blue, however, its brute force is derived (primarily) from lots and lots of data rather than lots and lots of processing power. Unlike Google and Facebook and Amazon, however, most enterprises do not have lots of data (relatively speaking) in their data centers. Their solution will be to take their own (meager) volumes of data and synthesize it to create the amount of data required for training their algorithms and validating their models. Synthetic data will graduate from its role as a sub-set of anonymized data to play a new one in the training of deep learning algorithms in data-challenged enterprises.

The business of data will become a significant sector of the global economy

Google and Facebook have led the way in showing the world you can build a very large and profitable business based solely on the collection and analysis of data. But their revenues are derived almost exclusively from serving as an advertising platform and the value of their data to their business is measured in relations to advertising efficiency and effectiveness. In the coming decade we will see more and more businesses, some growing quite large, whose sole business is data as an asset that has a defined intrinsic value and can be bought, sold, serviced, and added (as a distinct component) to other products and services. This will also be true for many enterprises that will come up with metrics to measure the value of data to their business and ways to “monetize” it, i.e., make it a distinct revenue stream. And the sub-sector of the data economy known as cyber crime will continue to grow by leaps and bounds.

The most successful and well-paying jobs will be data-related

From data preparation to perfecting data analysis models, the most important jobs of this coming decade will be related to data, its management and protection, its governance and monetization, its analysis and role in decision-making. In addition to the establishment and proliferation of data-related jobs, “data literacy” will become a major focus of internal training for all employees in many enterprises. Almost all products and services will either be based on data or will have a data component and their developers, managers, and sellers will have to be data proficient.

We will continue to trade our data privacy for convenience, entertainment, and feeling connected

Regardless of new government-mandated data privacy policies, our deliberate or unwitting or forced data nakedness will ensure the continuation—and possibly acceleration—of the data mining and monetization by enterprises and government agencies (such as DMVs in the US). “Other people’s money” will be dwarfed by “other people’s data.”
In the coming decade, buzzwords will come and go, but data—its growth, analysis, and use—will be the most significant and consistent tech trend. Ones and zeros will continue eating the world.

https://www.forbes.com/sites/gilpress/2020/01/06/6-predictions-about-data-in-2020-and-the-coming-decade/?ss=ai#63a8163d4fc3

Easy Ways to Boost Your Mobile App Testing Skills

December 17th, 2019 by blogadmin No comments »

The mobile application testing continues to be an integral part of the job of almost any skilled QA Engineer. Most professionals use a wide range of advanced utilities and mobile testing tools for making the testing process as precise as possible. Is there any universal software for application testing most companies use? What is the best way to improve QA management in your company? We’ve collected a number of must-have solutions for making the testing process easier, deeper, and much more effective.

Top Tools That Will Improve Your Testing

Emulator and simulator software. These are incredibly handy solutions for those testers, who have a limited number of devices. You don’t need to obtain all iPhone versions to test the app on iOS gadgets – professional emulator is always ready to help. The most popular programs for making UX/UI testing and other types of tests for various types of devices are XCode, AVD, and Genymotion. However, these are the most expensive solutions compared to crowd testing services, real devices and real people.

Note: Although testing on virtual devices can provide you with tons of useful information, using physical devices is still preferable. This way, using the services of a crowd testing company might be a great option.

Network configuration tools. The performance of modern devices is tightly connected to the type of network they use. Therefore, it is important to have special tools that will allow you to configure its settings. Network configuration tools will be exceptionally useful in case you need to imitate a bad Internet connection or lost data packets. Network Link Conditioner is likely to become the best solution for making advanced network settings for most types of gadgets. If you are looking for proxy testing tools, it might be a good idea to try Charles or Fiddler. By the way, don’t forget about API testing utilities: Postman, Insomnia, Paw, and others.

Automation testing solutions. Most experienced testers will tell you that Selenium is the leading program for performing automation testing. However, this is not the only solution for making tests in a fast, reliable, and top-notch way. In case you are new to automation testing, it is recommended to begin with Appium. This application is more user-friendly to beginners and will help you learn the basics of performing the automated tests. Among the other good alternatives, there are Kif, Robotium, and Frank.

In case you need a tool, focused on mobile operating systems, consider choosing XCUITest for iOS devices and Espresso for Android. These two are easy-to-use and configure that is highly valued by most beginners.

Manual testing. This is the process of manually testing software for defects and it should not be ignored, especially in digital testing. By playing the role of the end user and using most of the features with real devices, under real life conditions – you can provide extremely valuable feedback. Manual testing should be the first thing to test on a new product (before doing any automation) and it’s a necessary step to check the automation testing feasibility. Manual testing does not require any special tools, but it’s recommended to use good reporting tools such as Jira, YouTrack, RedMine, Ubertesters and many more.

Exploratory testing. Writing standard test cases is good but not perfect for some projects. Therefore, some expert QA Engineers perform exploratory testing aside from classical test cases to better understand the app’s weaknesses. With exploratory testing, you can find bugs and crashes in completely unexpected places and conditions. The exploratory testing is one of the most important types of testing services. As a rule, you don’t need to do anything to order this kind of service – the entire testing job is done by professional QA Engineers.

Beta testing tools. How will a certain app behave when you install it from the store? Will everything be okay in case you decide to update it from the current version? To check these features, you will surely require some professional tools for beta testing. Test Flight is one of the greatest apps for these purposes. Another alternative is the Ubertesters beta testing management platform. The platform allows you to also distribute your builds among testers, get crash reports, video recording of the test sessions, manage the testers and much more.

Note: beta testing tools such as TestFlight usually require having a certificate for the app, so don’t hurry up to use them in the early stages of your project. The Ubertesters platform does not require to pre-approve the app in the store, thus, it might be a better alternative for build distribution and a beta testing tool.

Alpha testing tools. Almost any test case requires using Alpha testing. The truth is that this type of testing is really useful before the release and on the early stages of development. If you don’t know where to start, it is recommended to try the most popular solutions that are widely used by most experienced testers. AppBlade, Ubertesters, Google FireBase, and HockeyApp are among the greatest options for Alpha testing.

Application analysis software. These tools are great for reporting bugs and crashes with the help of simple and comprehensible charts and diagrams. Different tools have various advanced functions, so it is better to test a few programs to find the best one to suit your needs. AppSee, CrashLytics, and FireBase are among the leading application analysis tools that are available on the market. Each one is unique and focused on different testing areas.

Pro Tips for Better Testing Results

Device rotation. Always try to rotate the device when performing certain types of test cases. It might be really disappointing to find out that the app completely crashes when you just rotate the position of the smartphone.

Change location. If you are testing some features that are connected with time or language (for example, some apps that offer delivery services), it is greatly recommended to try switching these options to make sure everything is working properly.

Notifications. Notifications is another feature that requires more precise testing. Don’t stop with only displaying the notifications – it is also important to test the possible interactions and send the user to the required screen or app.

Responsive testing. Responsive testing is designed to check whether your application perfectly fits screens of different kinds of mobile devices, such as smartphones and tablets. It is recommended to test your app on real devices with various screen sizes.

SAP Data Intelligence: Enterprise AI Meets Intelligent Information Management

November 5th, 2019 by blogadmin No comments »

Artificial Intelligence has struggled to live up to the hype of recent years.

If you were to believe the buzz, AI would be responsible for automagically solving all our biggest problems with complex computer wizardry and granting all of us a life of leisure and simplicity. It reminds me of the Hitchhiker’s Guide to the Galaxy, in which hyper-intelligent beings design a computer to reveal the answer to the meaning of life, the universe, and everything–only to find out that the answer is 42, and they never knew what the original question was anyways.

At the same time, Information Management approaches have failed to keep pace with technological change. Most of this technology was built and designed for the days of on-premise applications that wrote to on-premise databases, where the goal was to extract data and load it into a data warehouse for BI and reporting. While that need still exists, the data that we manage and the ways we extract value from that data have all radically shifted and diversified.

We are left with a complex mix of structured, unstructured, and object store data residing in a blend of cloud and on-premise systems, with access often being limited or non-standardized via APIs. The result is a complicated landscape of data sprawl, tooling diversification, and data siloes. All of this leads to an increasing inability to “locate the wisdom we have lost in knowledge” and the “knowledge we have lost in information” (all credit where it is due to TS Elliott).

Where Traditional AI and Information Management Fail

The combination of this failure of AI and Information Management can be seen in a few data points:

• 86% of enterprises claim that they are not getting the most out of their data
• 5 out of 10 early data science initiatives fail to get to production
• 74% say their data landscape is so complex that it limits agility

And perhaps most telling: 2/3rds of businesses consider machine learning and AI important business initiatives but only 1/3 or less are confident in their ability to implement them.

Unlocking the Promise of Enterprise AI

This is why we have developed an entirely new solution from the ground up, with open source and cloud principles in mind, to ask how you tackle these challenges in order to unlock the true promise of Enterprise AI and achieve Data Intelligence. Data Intelligence is what happens when you bring together both halves of the equation: managing your data wherever (and whatever) it is, and then extracting value from that data using the latest tools and techniques.

https://blogs.saphana.com/2019/07/15/sap-data-intelligence-enterprise-ai-meets-intelligent-information-management/

3 Ways Artificial Intelligence Is Uprooting Sales

September 24th, 2019 by blogadmin No comments »

In 2015, Forrester caused a storm to brew when it announced that artificial intelligence (AI) would replace one million B2B sales jobs by 2020. This bold headline, however, failed to capture the entire picture. Sure, if sales reps continue to rely on age-old practices like cold calling and distributing spray-and-pray marketing collateral, their days are surely numbered. Yet, on the other hand, artificial intelligence has failed to live up to business expectations. Case in point: according to a recent white paper by Pactera Technologies and Nimdzi Insights, 85% of artificial intelligence projects fail to deliver on their intended promises to business. Artificial intelligence and human sales reps are not mutually exclusive entities. If sales reps adapt and exploit the ever-increasing capabilities of AI, they seek to gain from the emergence of AI.

Automating repetitive tasks

The majority of a sales rep’s time (63%) is consumed by non-revenue-generating activities. AI has enormous potential to free up sales reps’ time so that they can focus more effectively on selling, building relationships, and closing deals.

According to McKinsey, about half of a sales rep’s workload consists of activities that can be automated by AI. Consider, for example, time management and scheduling. Less than one third (28%) of sales reps adhere to a structured time management methodology. AI-powered scheduling and calendaring solutions go a long way in terms of transforming time management into time intelligence. Woven, for example, is an AI-powered calendar app created by Tim Campos, the former CIO of Facebook. Woven uses natural language processing to scan users’ email inboxes for signs of meeting requests. Its virtual assistant then generates suggested times to meet and sends emails to attendees to select a time option. The app even uses location data to account for travel time between meeting destinations.

Taking it one step further, it’s not all that hard to conceive of an app that gives sales reps recommendations as to how they should prioritize their days, depending on their chronotype.

In addition to scheduling, sales reps squander hours each day on email. The majority of sales reps’ time is spent on sales technology (62.8%), with sales-related email ravaging most of their time (33.2%). AI-powered apps can liberate sales reps from living in their inboxes. Crystal Knows, for example, uses AI and natural language processing to predict customers’ personalities and, in turn, create personalized email templates that will garner the best responses. It offers sales reps recommendations for specific language and phrasing, thereby saving them a lot of time scribing emails from scratch.

Identifying the best leads

Lead scoring is at the heart of any successful demand generation strategy. Enhancing lead scoring capabilities is top-of-mind for sales and marketing professionals alike. While lead scoring methods have become more refined, we’ve only scratched the surface. Only 17% of organizations rate their lead scoring initiatives as highly effective. Today, most leads that are passed from marketing to sales are of decent quality, but are not sales-ready. According to research by Demand Gen, an eye-popping 70% of marketing executives believe that the leads passed to sales are of decent quality, but many are not sales-ready. The result is that sales outreach is subpar. This speaks to why 50% of sales time today is spent on unproductive prospecting.

Enter AI. AI can monitor an arsenal of different signals to predict a specific lead’s readiness to purchase. Research by Gleanster Research reveals that half of leads are qualified, but not yet ready to buy. AI can unearth the lucrative sales-ready leads. B2B consumers are using more channels to engage with vendors than ever before—from review sites to social media platforms to online communities. AI can mine these platforms for buying signals, couple them with demographic, firmographic, and technographic information, and pinpoint which leads are sales-ready. It can account for nuances such as sentiment to predict buying propensity. In an ideal world, AI allows sales reps to transition from predictive to prescriptive selling by isolating why a lead is a particularly good fit.

Less than half of sales reps have data insights on customers’ propensities to buy. Yet, according to Harvard Business Review, companies that use AI for sales are able to increase their leads by 50%. AI helps eliminate the guesswork and empowers sales reps to focus their time most productively.

Enhancing customer relationships

A close read of Forrester’s report reveals that AI will affect different types of sales professionals differently. For “order takers”, who process customer orders that could be filled via self-serve channels, for “explainers”, who provide buyers with information about complex products, and for “navigators”, who help buyers understand what their companies need to purchase, job loss will be 33%, 25%, and 15%, respectively. But, for “consultants”, who help buyers understand what they need to purchase and who have vast knowledge about the buyer’s company, there won’t be any job loss. In fact, this subset will witness a 10% gain in available jobs.

The sales reps of the future will be a different breed compared to their ancestors. They will assume the essential role of consultants and advisors, leveraging AI to gain the trust and favor of customers. 79% of business buyers say it’s very important or absolutely critical to engage with a salesperson who is a trusted advisor and who adds value to their business. With a deeper understanding of customers’ needs, sales reps will be able to have more relevant and engaging conversations with customers. With knowledge of customers’ pain points, their reasons for buying, what obstacles need to be overcome, and which decision-makers are at the table, sales reps can creatively solve complex business problems that customers face.

We’ve come a long way since the term “artificial intelligence” was coined in 1955. Only in our current era has the sales profession started to realize the potential of AI. Contrary to some media headlines, AI will never uproot sales professionals entirely. The sales professionals of the future will work in tandem with AI, exploiting—and embracing—its capabilities to acquire new superpowers. Businesses that combine AI with human insights witness a 66% boost in productivity and a 61% increase in customer satisfaction, according to research by Forrester. The key is the marriage between AI’s IQ and humans’ EQ.

https://www.forbes.com/sites/falonfatemi/2019/09/19/3-ways-artificial-intelligence-is-uprooting-sales/#38ce05704df1

On-Premise and Cloud United with SAP Data Warehouse Cloud

September 17th, 2019 by blogadmin No comments »

In implementing a cloud-based data warehousing solution, how can on-premise and cloud work together seamlessly? What do you do if you have an on-premise database already? Do you have to move all your data to the cloud? You have questions, and we have answers.

SAP Data Warehouse Cloud addresses some of the core challenges that businesses face when it comes to managing reporting and analysis in modern data environments. It provides pre-built templates, integration to SAP and other data sources, and the power and flexibility of SAP HANA in-memory processing to ensure agility, speed, and simplicity.

SAP Data Warehouse Cloud is enterprise functionality made simple. Data marts and other data warehousing solutions are easy to build, allowing for faster implementation. Plus, SAP Data Warehouse Cloud removes barriers for departments, regions, divisions, or individual business users‒allowing them to set up data marts for projects and proactive research as needed.

SAP Data Warehouse Cloud’s simplified user interface makes it accessible to business users in a way that data warehousing solutions typically are not, giving a new level of access and control to the people who are closest to the data. It makes it easy to deliver a completed analytics solution that is flexible both in scope and access. And, critically, SAP Data Warehouse Cloud addresses the challenges associated with implementing a full cloud-based analytics solution whether data is located exclusively (or predominantly) on-premise, in the cloud, or in multiple clouds.

Getting to the Cloud

Introducing a cloud-based data warehousing solution in an environment where some or all of your data is currently on-premise raises questions about how the two environments can be made to work together successfully. What happens to the on-premise databases? Do you have to move them to the cloud or maintain copies of the data in two places?

The short answer is no—you don’t have to move it. That data can stay where it is, on-premise. SAP Data Warehouse Cloud can not only be used as a standalone cloud tool; it can integrate seamlessly with all your on-premise systems (whether they be SAP or non-SAP systems). You can either move the data to the cloud or access it remotely.

But “remotely” means something different where SAP Data Warehouse Cloud is concerned. The system provides simplified administration with centralized visibility and governance. This means that although the data may be located in two (or two dozen) different locations, it is being governed from one central point. The data warehouse cloud workflow concept treats the entire distributed data architecture as a single entity. It is your data repository. From an analytics perspective it is the single source of truth.

Finding the Balance

This allows organizations to find their individual balance between on-premise and in the cloud. Organizations with large on-premise databases don’t have to move to the cloud in a “big bang,” but can (for example) use SAP Data Warehouse Cloud to allow business users to extend the data provided by IT on-premise with their own data to conduct specialized reporting or analysis. This gives business users a cheap and flexible environment to conduct their individual analyses based on high quality, governed data from IT without interfering with the more stable IT backend systems. (Alternatively, an IT department can use SAP Data Warehouse Cloud to build new scenarios in the cloud—based on or combined with data they keep on-premise, allowing for an evolution into a full-fledged cloud data warehouse over time.)

Enabling business users to set up their own environments may be reminiscent of the classic “shadow IT” dilemma. But this is far from shadow IT. As Stefan Hoffmann outlines here, SAP Data Warehouse Cloud eliminates the painful security, trust, data quality, and other issues that come with shadow IT. It provides a new model of collaboration between IT and the business, in which the business has the flexibility and independence it needs while IT maintains the centralized governance that prevents chaos.

SAP Data Warehouse Cloud makes that evolution a smooth transition or a smooth series of transitions. For organizations looking to ultimately migrate to the cloud, SAP gives the option of defining as many steps along the way as makes sense for that enterprise. There are many possible hybrid configurations between a pure on-premise environment and a pure cloud environment, and SAP Data Warehouse Cloud supports all of them. You can take it fast or take it slow. The move to the cloud can be as agile, as gradual, and as incremental—or as accelerated—as makes sense for your business.

https://blogs.saphana.com/2019/07/08/on-premise-and-cloud-united-with-sap-data-warehouse-cloud/

Inclusive Leadership: How Joerg Wagner Uses a Future-Oriented Approach to Drive Inclusion

September 10th, 2019 by blogadmin No comments »

Joerg Wagner is SAP’s Global Head of Consumer Industries and is involved in retail, consumer products, wholesale and life science for Digital Business Services and manages in this role 310 direct and approximately 200 indirect reports across the globe. He is also in charge for SAP’s location in St. Ingbert with 750 employees and has been with SAP for 29 years. He has found that a massive global team requires an equally massive commitment to diversity and inclusion in everything they do.

Inclusion is at the heart of Joerg’s initiatives with his team, and he credits the sense of trust he has built with his team for his ability to foster inclusion. Respect, trust, and honesty are all key tenants of Joerg’s leadership style, all of which led to his high leadership trust index far above SAP’s average. “How we deal with people and how we respect them should be two of our utmost priorities,” he went on to say.

• Has very high leadership trust index and has been with SAP for 29 years
• Values a trusting environment that gives employees the “freedom to fail”
• Has a diverse team with colleagues in Latin America, Spain, Canada, and Europe among others while women comprise 40% of his leadership team

When asked about how he achieved his high trust index, Joerg discussed his inclusive behaviors and said, “You need to be approachable, and you need to have an open-door policy and talk to everyone to make everyone feel welcome.” Joerg also credited giving his team freedom to make decisions and avoiding micromanaging, which are two integral aspects of his methodology. He aims to give employees the freedom to fail in order to drive innovation and find unique solutions.

Joerg values the freedom to fail because he believes it coincides with a freedom to grow. He believes a trusting environment is one that naturally lends itself to freedom and innovation, and he views micromanagement as a hindrance to freedom. Avoiding micromanaging empowers his team and Joerg believes, “If you micromanage, that means you lack trust.”

The sense of trust on his team is also a result of Joerg’s efforts to appear more as another team member than a manager. He also works to keep his communication style consistent regardless of his audience. Moreover, Joerg consistently steps outside of his comfort zone and meets new people to further his inclusion and collaboration capabilities. For example, he always sits at a different table with different people when he eats lunch. He says this is especially useful given his office location in Germany which sees newcomers daily. It gives him the opportunity to meet new people and learn what’s going on in other areas of the business.

Joerg’s team is a diverse one geographically, generationally, and in terms of gender. He has managers in Latin America, US, Canada, Asia, Switzerland, and Germany. Additionally, women make up 40% of his leadership team. Joerg says the diversity on his team has been extremely beneficial to the environment he attempts to cultivate since as he mentioned, “It creates an environment with a combination of rationale and empathy which is immensely helpful.”

Part of Joerg’s team diversity includes his focus on generational diversity – an approach that he thoughtfully refers to as, “future-oriented”. This future-oriented approach involves being flexible and focusing on a variety of communication methods such as What’s App, Instagram, Slack, or MS Teams as opposed to using email as a primary communication method.

Joerg tries to avoid hierarchies and ensures that students, interns, and new hires get visibility. When Joerg’s team hires students, the team hosts meetings where students can introduce themselves and share what they do. Joerg is also well-aware that while younger generations have less experience they have also grown up with technology and might be considered more digitally native than some of more senior developers. To take advantage of the skills of experienced developers and the digital insights of his younger talent, Joerg’s team pairs students and new hires with developers and consultants who coach them as both parties give and receive feedback.

In the future, Joerg aims to increase collaboration and drive inclusion across board areas as he views such collaboration as instrumental for achieving SAP’s future goals. Joerg envisions a future where different board areas are connected, and silos are non-existent. He remarked, “If you want to deliver the Intelligent Enterprise to customers, there is no one organization that can do this alone because you need the combination of every asset and brain, and you need to bring all of that together to deliver the best innovation to customers.”

https://blogs.sap.com/2019/09/09/inclusive-leadership-how-joerg-wagner-uses-a-future-oriented-approach-to-drive-inclusion/

SAP HANA – Hybrid Deployment Freedom of Choice for All

September 3rd, 2019 by blogadmin No comments »

With data sources branching out — thanks to the Internet of Things, artificial intelligence use cases, and more — one thing has become clear: enterprises need the freedom to choose multiple deployment options. On-premise. In multiple clouds. Between clouds.

But using existing application integration tools like integration platform-as-a-service (iPaaS) or an API management system can be complex, especially if you need to extend thousands of workflows to the cloud or massively scale to support an IoT solution. Additionally, hyperscale cloud providers have a vested interest in making their services sticky and proprietary.

The solution: a hybrid integration platform that is open, flexible, and agile. The 2019 spring innovations of SAP HANA provides just that — a universal hub for running SAP HANA applications across multi-cloud, hybrid, and on-premise environments.

Integration Complexity and Lock-in

The hyperscale cloud providers deliver a great service. You don’t have to worry about buying, upgrading, and otherwise supporting hardware; handling software refresh cycles; reducing downtime; and providing myriad tools, security, or support. But if you want to move an application or service to another cloud or managed services provider, it’s a hassle. You have to do a lot of rework at the infrastructure layer to re-provision those apps or services on virtual or physical infrastructure.

According to research by Gartner, through 2020, that type of integration work will account for 50% of the time and cost of building a digital platform. So, by 2022, at least 65% of large organizations will have implemented a hybrid integration platform. Such platforms will simplify, accelerate, and lower the costs of integration and introduce self-service capabilities for lines of business, subsidiaries, application development teams, and business users.

To-date, early attempts at hybrid integration platforms have had functional gaps that don’t solve all of the integration challenges. They don’t span all of the required user personas, integration domains, endpoints, and deployment models. For some SAP HANA customers, that has meant installing separate hardware for development, testing, and production for multiple cloud and on-premise deployments.

Achieving Hybrid Deployment Freedom and Agility

Most enterprises want to be able to extend their SAP HANA presence from their data centers to the clouds of their choice quickly and easily. They want to use the power of virtualized assets to query data sets wherever they are.

The most recent release of SAP HANA delivers a hybrid integration platform that lets you integrate premise-to-premise, cloud-to-cloud, and premise-to-cloud using process orchestration and cloud integration capabilities. With hyper-converged infrastructure solutions from SAP HANA-certified hardware partners like Cisco, Dell, Fujitsu, HP, and Lenovo, it’s easy to connect to all of your data and manage allocations of virtual compute, storage, and network resources.

Future-proof Your Data and Analytics Infrastructure

Look at what integration capabilities already exist within your organization. Are these solutions able to support your hybrid on-premise/cloud deployment needs going forward? Can they support integration for advanced analytics and IoT solutions that need to tap into multiple data stores, scale geographically, and handle huge data volumes and complex queries?

It’s important to keep in mind that today various departments within organizations are recognizing the power of data and analytics to lower costs, add revenue, seed new business models, and compete more effectively. IT should aspire to provide an environment that fosters experimentation by diverse stakeholders who have ideas for new services and applications. Most such initiatives will require integration with core IT systems, cloud services, and perhaps data silos.

Multi-cloud and hybrid cloud integration capabilities preserve your freedom to choose the best cloud service provider today and in the future. A hybrid integration platform gives your organization the flexibility to quickly expand to new geographies, to embrace new application development paradigms, and to take advantage of cutting-edge products and services from cloud innovators.

SAP HANA helps you keep all of your options open with powerful integration capabilities. Hyperconverged infrastructure means you don’t have to lift and shift your development environment into proprietary cloud or on-premise frameworks. You can choose the infrastructure, software, and cloud partners you want when you want them. You can switch to others, as needed. This is the essence of agility and freedom of choice in a dynamic world that is continually in flux.

https://blogs.saphana.com/2019/04/30/sap-hana-hybrid-deployment-freedom-of-choice-for-all/

SAP Cloud Platform’s Role within SAP’s Digital Platform

August 27th, 2019 by blogadmin No comments »

The law of today’s business jungle is innovation – and SAP Cloud Platform and a multi-cloud strategy give you the agility to continuously adapt.

Keeping up with the relentless pace of business innovation and the technology that fuels it can be a daunting task. With constantly shifting customer expectations and an abundance of new applications that are easier than ever to adopt, enterprise technical landscapes are transforming on an almost daily basis.

So how do SAP customers keep pace? I think my colleague Irfan Khan said it best—the key to surviving and thriving in the twenty-first century business landscape is “a compelling digital foundation that not only unifies data systems and processes, but readies customers to continuously adapt to evolving business and technology conditions.”

The SAP digital platform draws on decades of SAP business process excellence and includes the integral and unifying SAP Cloud Platform—an innovation powerhouse for the integration, extension, and creation of corporate applications. The SAP Cloud Platform is a game changer for over 13,700 customers, representing companies of all sizes and industries all over the world. Distinguished by a modular, incremental approach, SAP Cloud Platform enables small, quick integration and extension projects that deliver value in only a few short weeks, or even in just a few days. After achieving near immediate measurable benefit on smaller projects, customers are increasing the scope and coverage of SAP Cloud Platform adoption to tackle bigger and more mission-critical application services projects.

An Integration and Extension Platform Supported by Business Services

The SAP Cloud Platform covers all aspects of integration, from SAP cloud applications to on-premises landscapes (and vice versa), to most major third-party solutions. Today’s enterprise landscape reality is a hybrid one—with on-premises solutions still heavily relied upon even as both SAP and non-SAP cloud application consumption rapidly rises. Our suite of integration options, along with prepackaged integration flows and business connectivity with third-party applications and APIs, allows customers to securely connect people, processes, data, and devices both inside and outside your organization.

All organizations need to distinguish themselves from the competition, and the SAP Cloud Platform plays an outsized role in helping businesses differentiate from the pack. Whether it’s adding custom settings to a new third-party cloud application or configuring an existing on-premises solution to meet new business challenges, SAP Cloud Platform provides productive and integrated approaches to extend existing cloud or on-premises solutions and applications.

Underpinning the platform’s key integration and extension functionalities are an enriching set of business services—including Analytics, Blockchain, Internet of Things, Master Data, Orchestration, and so much more—which help create a harmonizing layer of agility that spurs intelligent business solutions based on functional logic, which then stimulate growth and innovation.

Promoting Collaboration

SAP Cloud Platform also delivers an unparalleled, much needed collaboration between IT and decision-makers within the lines of business—a long-standing dilemma in our industry that, thanks to SAP Cloud Platform, might soon be a thing of the past.

Multi-Cloud Strategy

SAP Cloud Platform is based on open standards and supports multi-cloud environments, offering complete deployment flexibility and control for any cloud infrastructure, whether from SAP or from the major hyperscalers like Amazon Web Services, Microsoft Azure, and Alibaba Cloud. Customers expect compatibility with their choice of cloud deployments, and SAP Cloud Platform delivers by focusing on integrating and extending applications, data, and processes, regardless of the backend infrastructure.

The Road Ahead

As an indispensable element of the SAP’s business technology platform, SAP Cloud Platform fuels corporate agility for quick and intelligent reactions to market conditions. Flexible integration and extension capabilities allow SAP Cloud Platform customers to integrate, extend, connect and differentiate in order to not only keep pace with the head-spinning speed of change in the digital age but also to adapt and evolve, keeping one step ahead of whatever tomorrow may bring.

https://blogs.saphana.com/2019/07/09/sap-cloud-platforms-role-within-saps-digital-platform/

How AI can transform Enterprises?

August 20th, 2019 by blogadmin No comments »

Artificial Intelligence, more popularly known as AI, might no longer be the new technology on the block, but it is ‘the’ technology that everyone is talking about. Facial recognition, digital assistants, autopilots etc. are examples of the existing AI around us. AI is emerging as that disruptive technology that will change the way we live and work. While AI has been seen often in a consumer-centric world, the enterprise too is warming up to this technology.
2018 witnessed widespread adoption of AI in different industries as organizations realized the value AI brought to the table – be it in improving operations, assisting the data analytics drive, boosting innovation, and improving customer experience amongst other things. Owing to the immense value AI brings to the table, the global AI market size is expected to reach $169,411.8 million in 2025, from $4,065 million in 2016 growing at a CAGR of 55.6% from 2018 to 2025 according to MarketWatch.
So, what transformative value does AI bring for the enterprise? Here’s a look at how AI will transform enterprises and change the future of work.

1. The New age of Automation: AI is going to give automation the boost that it needs. As enterprises look towards technologies such as Robotic Process Automation (RPA), with AI we shall be moving into the world of Intelligent Process Automation. IPA combines process automation with Robotic Process Automation (RPA) and Machine learning (ML) and creates choreographic connections between people, processes, and systems. IPA will not only automate structured tasks but also generate intelligence from process execution.
IPA is all set to increase the level of transparency in business processes, optimizing back-office operations, increasing process efficiency and customer experience, and improving workforce productivity considerably. Along with this, IPA also holds the promise of reducing costs and risks and promises more effective fraud detection. Owing to these benefits, the IPA market is expected to be worth $13.75 billion by 2023.

2. The Rise and Rise of Chatbots: The friendly chatbot has already made some inroads into the enterprise. With AI, the chatbot invasion is going to become more pervasive in the enterprise of the future. Customer-facing industries such as retail, healthcare, banking, and financial services shall witness the rise of AI-powered voice assistants such as Alexa or Siri to create interactive experiences for the customer without pushing the load of delivering exceptional customer experiences on the staff alone.

Chatbots will also become the norm to service the internal customers of the organizations, the employees. Enterprise chatbots will be powered by AI technologies such as NLP (Natural Language Processing), semantic search, and voice recognition. They will enhance search capabilities and deliver a new way for employees to interact with corporate data to improve their productivity.

3. AI and the UX Impact: The focus on User Experience or UX is only going to keep increasing. With AI, the user experience will not be driven by guesswork but by faster analysis of the right data, by the enterprises in the future. User experiences with software products, even within the enterprise, have to mimic consumer-grade experiences.
Fluid, intuitive, efficient, and highly-personalized user experiences are going to be the norm. UX is also going to be the defining factor in product success and acceptance. Enterprises will look at the insights provided by AI by intelligent information gathering and identifying patterns to deliver greater value to the end-user. This will make the user experience of products highly intuitive and intelligent as well.

4. Greater Intelligent Customization Capabilities: As we move deeper into the age of personalization, enterprises will have to look towards technologies such as AI to develop intelligent customization capabilities. Data is already improving the customization capabilities of enterprises.
With cognitive technologies such as AI, they will be able to further improve their customization capabilities and create products that individual users will love. Leveraging user data and faster data-processing capabilities, AI can speed up interactions and provide intelligent insights to develop products and solutions that can be highly customized to meet user demands.
5. Cutting Edge Analysis To Bolster Data-Driven Decisions: AI will be leveraged in the enterprise to perform advanced data investigation in less time to improve business process, product, and service efficiencies. AI technologies have the capability to analyze usage patterns and then deliver deep insights that will take data-driven decision making to the next level.
Whether it is for predictive maintenance or predictive analytics for product development, or risk management or planning, the AI impact will make the enterprise smarter and more proactive in its decision-making.

6. AI In Software Development and Testing: Software Development and Testing will also feel the AI impact as this technology gets more pervasive. To respond to the market need for robust, reliable, and high-quality software that is delivered faster, AI technologies will get ingrained into the development and testing lifecycle.
With self-learning algorithms that are designed to self-improve, enterprises will be looking at improving the efficiency of the process of software development. They will leverage automated code-generation, among other things, and achieve a shorter time to market with greater confidence.

While AI has met with a certain resistance in the past, the coming years will see this technology achieve greater maturity. Given the immense value that AI can deliver, it is only a matter of time before AI will become a necessity for the enterprises that wish to remain relevant in this ever-evolving and competitive marketplace.

https://www.thinksys.com/ai/ai-transform-enterprises/

Are we set for the Blockchain Age in Data Storage?

August 13th, 2019 by blogadmin No comments »

Although Blockchain came into the limelight with the cryptocurrency bitcoin, in the last year or so, companies have become increasingly aware of how Blockchain can bring about transformation across industries. With the cloud storage market expected to grow to $88.91 billion by 2022, the decentralized storage industry is rapidly gaining popularity, and Blockchain will be critical to its success. Since data storage – especially critical financial data – is always vulnerable to security breaches, migrating data from private data centres onto public Blockchains can help enterprises decentralize storage, thereby enhancing availability, scalability, and security of data.

Current Challenges:

It is not hard to imagine the ever-increasing volume of financial data that is being generated. Data, which will also then have to be managed, stored and analyzed for effective business decision-making. Connected devices, mobile apps, and the increasing need to share data across businesses are all contributing to the increasing demand for storage that is highly available, scalable, and secure.

Businesses that are looking to launch new, data-driven applications face a sea of challenges with respect to time, effort, and management to provision new datasets and databases.

Traditional cloud storage networks are also known to come with latency challenges. Since most of the time, the data that gets stored in a data center will not be in the same location as the business, delays in delivery are the norm – and that doesn’t work well in the financial context where delays of milliseconds can cause huge losses.

What’s more, the need for large databases also necessitates the need for managing large data centers, that require frequent temperature control, periodic updating, and rigorous upkeep -all expensive.

In addition, the road towards a richer, more data-centric way of working is further challenged by a global phenomenon of data breaches from centralized data centers. The outcome is worrisome – the growing storage needs of businesses are driving extraordinarily large volumes of data to be stored in centralized databases.

This creates risk at a scale never seen before. This necessitates the need for de-centralizing data storage, that can not only minimize the risk of a complete shutdown but also ensure efficiency and transparency of data storage.

The Benefits of Decentralized Storage:

As most current cloud-based databases are highly centralized, they are tempting targets for data breaches. Cloud Storage Companies do have several mechanisms in place to avoid the loss of data, such as dispersing duplicate files across various data centers to avoid a breach. That said, decentralizing storage would more or less eliminate the risk and repercussions of disruptions.

Although current networks need to evolve in order to accommodate such decentralized storage infrastructure, the day is not far when data will be supported by a network of decentralized nodes in a more user-friendly and cost-effective manner than the current, central database solutions.

Decentralized storage works by distributing the data across a network of nodes, thereby reducing the strain on a single node or database. Since it utilizes geographically distributed nodes, decentralized storage can avert such catastrophes and ensure the company’s data is always protected. As data is stored across hundreds of individual nodes, intelligently distributed across the globe, no single entity can control access – thus improving security and decreasing costs.

Any attack or outage at a single point will not result in a domino effect, as other nodes in other locations will continue to function without interruption. The distributed nature of these nodes also makes decentralized storage highly scalable, as companies can leverage the power of the network and achieve better up-time.

The Role of Blockchain:

Although one of the biggest achievements of the Internet era has undoubtedly been cloud data storage, it is already under threat of being replaced by Blockchain storage technology. As the need for decentralized storage becomes more and more relevant, the storage industry is looking to make the most of Blockchain’s distributed ledger technology.

Blockchain paves the way for user-centric storage networks, where companies can move data from the current centralized databases to Blockchain data storage, and benefit from a more agile, customizable system. Because storage gets distributed across nodes, companies can enjoy a better speed of retrieval and redundancy by accessing data from the node that is closest to them.

With such attributes that meet the practical demands of storing high volumes of data, Blockchain will partition databases along logical lines that can only be accessed by a decentralized application using a unique key. Such a decentralized network of storage nodes not only reduces latency but also increases the speed by retrieving data in parallel from the nearest and fastest node.

And because there are so many geographically dispersed nodes in a network, the reliability and scalability of decentralized storage are greater. What’s more, since the devices in the nodes aren’t owned or controlled by a single vendor but by several individuals, the availability and reliability of data are improved even further.

The Way Forward:

As industries battle issues of the security and confidentiality of data, the evolution of Blockchain has come like a boon. Touted as a technology with the potential to transform every industry, Blockchain could be particularly beneficial in the data storage game.

By improving business efficiency and bringing transparency in how enterprises store business data, Blockchain is poised to offer myriad benefits such as shared control of data, easy auditing, and secure data exchange. While it may take time for Blockchain to become the default choice for businesses looking to meet their ever-increasing storage needs, it won’t be long before the world opts for this secure, efficient, and scalable solution in an increasingly data-starved world.

https://www.thinksys.com/blockchain/are-we-set-for-blockchain-in-data-storage-age/