Trends of ERP Testing to Watch for 2019

ERP (Enterprise Resource Planning) systems no longer necessitate any sort of introduction. For businesses, investing in a good system no longer is an alternative. It is a necessity. Enterprise Resource Planning systems have been a part of the business software landscape for a long time. Ever since their foray into the world of business, vendors are incessantly evolving them, so they are more powerful, robust, simpler to use, and affordable.

The 5 Major ERP trends that we should consider in 2019:

1.Competition from Disruptors- The Enterprise resource planning behemoths that have conquered the industry are encountering stiff competition from new, often Software-as-a-Service (SaaS)-only startups & the proliferation of fresh trends threatening to upset how enterprises collect and process data, and also operate. Renowned companies like FinancialForce (already having more than 1,300 Enterprise resource planning customers) and Kenandy are creating solutions based on the Salesforce App Cloud to make them alluring to users of the popular CRM and sales automation tool. On the disruption side, data visualization, big data, and artificial intelligence (AI) top the list of newest technologies that threaten to alter the way Enterprise resource planning systems are built and used. Enterprises looking to update their Enterprise resource planning systems in the year 2019 will need to become aware of to how their new prospects handle such trends. Database performance will be the core performance indicator (KPI) for Enterprise resource planning in 2019.

2.Enterprise resource planning, SaaS, & Hybrid ERP- Enterprise resource planning apps are stored on your servers, which mean you are responsible for long-term hardware maintenance, hardware costs and data backup and recovery. SaaS-based applications are stored on cloud-based servers, which are much less costly, very fast to upgrade and scale, and don’t take up clunky servers. Hybrid ERP systems are becoming famous in some sections as long-time Enterprise resource planning customers enjoy the ability to move certain Enterprise resource planning functions to the cloud while sustaining tight, on-premises control over other facets, particularly those most vulnerable to compliance regulation.

3.Focused on Social Media and Digital Marketing- These days, Enterprise resource planning is specifically focused more and more on functions than marketing, but those modules will need to become social media-savvy by the year 2019. Future Enterprise resource planning systems will need to be able to integrate direct marketing & data gathering links across manifold social media channels to remain on the top list and highly competitive.

4.The Internet of Things (IoT) is going to stay- As more and more products and devices become connected to the internet, more data can be instantly funneled into the Enterprise resource planning system, and that’s an advantage that can’t be ignored. This trend offers better oversight over things like the supply chain and appliance performance, and it also gives overall data pool for good decision making.

5.ERP for the Subsidiary- As more Enterprise resource planning systems are being delivered via the cloud, it is becoming far easier to deploy such SaaS-based tools incrementally. Rather than replacing ERP whole-hog, big giant companies are selecting one slice of the business and plugging in SaaS Enterprise resource planning on a trial basis. This approach lets businesses observe SaaS Enterprise resource planning performance to evaluate how it might fit into the existing on-premises Enterprise resource planning implementation—or whether it should replace on-premises Enterprise resource planning throughout the whole enterprise.

How Big Data can be leveraged in all aspects of Testing?

Newest data technologies are entering the market; however, the old ones are also going strong. But it is also important to note here that the Big Data technologies adoption will never slow down, not in the near future. So, it is significant to note how we can overcome the challenges that come with this technology. Such technologies have gone beyond the realms of merely being a buzzword. It is now immensely adopted among corporate and companies, irrespective of size. As per the well-known research and advisory firm, “Big Data is high-velocity, high-volume, and/or high variety information assets that demand cost-effective, innovative forms of information processing that enable improved decision making, great insight, and process automation.” It truly forms the basis for machine learning & predictive analytics which is the best thing considering the very real occurrence of networks and enterprises being inundated with data from mobile apps, social, and IoT that produce a 24×7 constant flow of data.

Big Data has a variety of features. The three significant features of big data are:

  • Different types of data
  • Big volume of data
  • Speed and accuracy at which the data can be processed

What is Big Data Testing?

In simple language, Big Data refers to enormous quantities of data. There is no specific size parameter to define the size of this technology. It is safe and sound to assume that the standard method to measure it when comes in petabytes or terabytes. Data comes in from every direction, and the velocity and volume would be monstrous. Software developers will be able to build better software faster, using Machine Learning and Artificial Intelligence technologies like deep learning & natural language processing.

Benefits of Using Big Data Testing in All Aspects of Testing
Through Big Data testing, you can make sure the data in hand is accurate, healthy, and qualitative. The data you had collected from the variety of channels and sources are validated, assisting in better decision making. There are a number of benefits to Big Data testing.

  • Data Accuracy — One of the popular research & advisory firm speaks that data volume is likely to expand by 800% in the next 4-5 years, and 80% of this data will be unstructured. Just imagine the volume of data that you have to analyze. You need to convert all this data into a structured arrangement before it can be mined. Armed with the right kind of data, companies can focus on their weak areas, and be prepared to hit the competition.
  • Better Profit and Reduced Loss — Loss in business will be minimal or even a thing of past, if data is appropriately analyzed. If the accumulated data is of lower quality, the company suffers terrible losses. Separate precious data from structured as well as semi-structured information so no faults are made when dealing with clients.
  • Good Decision Making — When data gets in the hands of the appropriate people, it becomes an asset. So when you have the appropriate kind of data in hand, it would help you make smart decisions. It allows you to analyze all the threats and make use of only the data that will put into the decision making process.
  • Right Strategy and improved Market Goals — You can chart a better decision making plan or automate the decision-making procedure with the assistance of big data. Collect all the validated data, examine it, understand user behavior and make sure all of them are realized in the software testing procedure, so you can deal out something they need. Big data testing assists you optimize business strategies by looking at this information.

Conclusion

Transforming data with intelligence is a great concern. As big data is very important to a company’s decision-making plan, it is not even possible to begin asserting the worth of arming yourself with reliable information. Big Data processing is a very promising field in today’s complicated business environment. Applying the accurate dose of test strategies, and following best practices would help ensure qualitative software testing. The idea is to recognize and recognize the defects in the primary stages of testing and fix them. This helps in cost reduction and better outcomes. Through this procedure, the troubles that testers faced during software testing are all solved now as the testing approach are all driven by data. Hence, Big Data is a powerful tool for the current business. In fact, some believe that companies that fail to derive value from machine learning & Big Data will face huge competitive shortcomings as the field continues to grow and adoption increases around the world.