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IT Trends to Watch in 2021

TAKE NOTE (Insights and Emerging Technology)

The federal government, like its state and local counterparts, has been consumed with responding to the coronavirus pandemic in 2020 and its resulting effects on how work gets done. Agencies shifted to large-scale remote work setups and zero-trust cybersecurity became more important with so many users operating outside of the traditional boundaries of the federal enterprise. Experts and industry analysts say there will be a mixture of continuity and acceleration of existing trends in federal technology.

Here are some of the key trends to watch in 2021…

The Biden Administration Will Put Its Stamp on Federal IT
The most obvious and potentially significant shift that will occur in 2021 in federal IT is the transition to a new administration.

Loren DeJonge Schulman, vice president for research and evaluation at the nonpartisan Partnership for Public Service, home to the Center for Presidential Transition, believes that certain initiatives are likely going to continue.

The focus on modernizing tech is likely to continue under the Biden administration, Schulman says. “I’d expect that some of the major tech initiatives that the Trump administration put in place will also keep going, such as the development of new technologies and emerging tech like artificial intelligence or quantum computing, and also the focus on encouraging agencies to use technologies like this. I think they’ve actually had some really great effect with a lot of innovation during this COVID timeline.”

Remote Work Will Continue and Evolve
Federal IT leaders have indicated that they expect remote work setups that were expanded this past spring to be extended well into 2021 as the pandemic continues to unfold. That will likely require additional technology investments as agency IT teams look to maintain and potentially augment the capabilities available to users.

Zero-Trust Security Will Become Even More Popular
In August 2020, the National Institute of Standards and Technology issued the final draft of Special Publication ­800-207, on zero-trust architecture. It defines zero trust as “a cybersecurity paradigm focused on resource protection and the premise that trust is never granted implicitly but must be continually evaluated.”

Zero-trust cybersecurity has taken greater hold in the defense realm than in civilian agencies, but they are also considering it as well. Analysts expect zero-trust security to take deeper root in federal IT in 2021.

Cloud Migration and Application Rationalization Will Continue
One of the core tenets of the government’s Cloud Smart strategy is application rationalization, which involves reducing an application portfolio by assessing the need for and usage of apps and pushing to get rid of obsolete, redundant or overly resource-intensive applications.

There are many benefits to rationalizing application portfolios and modernizing applications by putting them in a cloud architecture. Those efforts will continue in various forms, analysts say, though the progress will likely come in fits and starts. Legacy modernization is still very much a work in progress for agencies.

AI Will Be Prominent, But Don’t Lose Sight of Other Emerging Tech
In August, the Trump administration unveiled a plan to invest $1 billion in AI and quantum computing. The Wall Street Journal reports that the Biden administration is likely going to continue such funding efforts.

Citing Robert D. Atkinson, president of the Information Technology and Innovation Foundation, the Journal reports that the “Biden administration is expected to invest more money in AI and quantum information science, in part because overall spending on research and development is expected to be higher.”

Dave McClure Principal Director of Federal CIO Advisory Services for Accenture Federal Services believes in 2021 the federal government, “will encounter a technology inflection point, and CIOs need to radically optimize the use of these new tools in ways that can help address changes in service delivery deriving from a digital operating model focused on customer experience.”

Awareness of emerging tech is high in government, but adoption is relatively immature, according to McClure. Agencies have been more adept at adopting open-source software development, DevSecOps and microservices architectures because the benefits of those can be easily quantified in terms of faster software delivery times, for example.

“Where agencies are gaining differentiated mission or customer value from an emerging technology, we believe continued investment should be prioritized, even if their peers are lagging,” McClure says. “Where peers are stumbling and struggling to gain value from an emerging technology, investment should likely be deprioritized until more stable and mature emerging tech identification, piloting and adoption practices are in place.”

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UNDER DEVELOPMENT (Insights for Developers)

SAP Intelligent RPA Explained

In The Beginning

RPA became a buzzword in the enterprise field in 2015. That’s not to say some form of it didn’t exist before that. As early as the 1990’s Macro and screen-scraping technologies came into being. Later in the 2000’s RPA tools developed out of the need to focus on the automation of a limited set of repetitive tasks in an individual industry-specific solution. The SAP-acquired Contextor was one of those pioneers.

Today, RPA solutions deliver that promise: they automate from old mainframe applications to classic Windows applications as well as modern web-based applications. Direct API accesses as well as being able to invoke data access protocols like SQL are also more and more common in modern RPA tools. RPA started to merge with other technologies like Machine Learning, SAP and industry call this Intelligent RPA.

What is Robotic Process Automation

RPA is basically a software where bots handle the work that is routinely done by humans. The intelligent bots or robots by one of the leading software developers, SAP, are developed on the principles of artificial intelligence and machine learning. These bots will replicate human action and reduce or eliminate repetitive or manual tasks. They also deliver high-volume, error-free work at high speeds. In doing so, RPA improves your operational efficiency, accuracy, and productivity while reducing operational expenses by approximately 70%.

The business fields that are most influenced by RPA include the healthcare, telecommunications, banking, manufacturing, logistics, and supply chain sectors. Here, the software handles revenue forecasting, data validation, report generation, customer relationship management, and data replication, among other tasks.

With all the benefits it has to offer, RPA is clearly here for the long run. Even so, some companies are reluctant to adopt the software believing it will not effectively handle the technological changes guaranteed to happen in the future. They assume that the technology is only focused on a narrow list of repetitive tasks and will not prove cost-efficient for their operations. While other software companies might not be as intent on improving different things on their RPA platforms, SAP has invested in several things that will transform the future of RPA and ensure it holds up to the technological changes in the ERP world. The changes are also meant to boost the benefits of RPA to businesses.

Below are a few trends which are worthwhile to explore further…

RPA Combined With Other Technologies = Operational Efficiency

The primary goal of RPA is operational efficiency, that is, making your company as time and cost-efficient as possible. Though revolutionary, RPA is not the only technology you need in a company to actualize efficiency. To reach end-to-end automation and maximize profits, it is best to combine RPA with other technologies. The typical tools combined with RPA are document information extraction ones like OCR. This is because most of the processes handled by RPA involve unstructured data like invoices, and it can be hard to enter this information into ERP systems. Moreover, RPA bots are generally short runners, whereas most business processes are long-running ones that need a few weeks to complete.

The combination of RPA with artificial intelligence and machine learning allows the training of complex business models to make decisions they would otherwise not have made with a rule framework.

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– Dig Deeper –

Q&A (Post your questions and get the answers you need)

Q. I am hearing ALV is changing in HANA. I now see IDA appended to the SALV classes. What is this IDA?

A. IDA stands for Integrated Data Access. To better understand this, let look at the classic (OLD) way of calling the SALV methods. The existing ALV is has more functionality on the application layer. That makes it very very slow. The full data is being selected and sent to the ALV framework, which translates that into display on the GUI container. check out our blogs on SALV.

Since the entire data is being selected beforehand, the framework has to parse the data as required. This can be very wasteful, lets assume you have set a filter which only displays a single record in an ALV output but the entire table was selected. Furthermore, you have a many records which you may be sorting in internal tables on the application layer.

With HANA database aka HDB aka in-memory DB, many of the operations which can be executed on the front-end can be send to the database – via code push-down. You can lean more about the code push-down paradigm in the blog The ABAP Developer Road Map to SAP HANA

Lets take a closer, albeit 5000 foot, looat at IDA and SALV.

The new SALV IDA (Integrated Data Access) works more on code push-down concept. Means, you don’t select the data and send that to the ALV, instead you generate the ALV for the DB table, DB view or a CDS views. Then, the IDA framework then analyze the required columns, analyze the filters to get the required where condition and executes the select query.

Additionally it also analyze the view port — the only visible section of the ALV — the visible rows and columns. Using this info, the framework would trigger a new query on the DB to get only those required data.

One thing to note, IDA ALV would work on any database but you many not get all the great performance benefits if you not using the HDB.

Below is an example of using a call for T100 to generate an ALV using IDA…

iv_table_name = ‘T100’ )->fullscreen( )->display( ).
CATCH cx_salv_db_connection
INTO DATA(lo_exc).
MESSAGE lo_exc TYPE ‘I’.



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