The Universal Model Framework
The Business Analyst Perspective:
In an ever expanding business world, business analysts are your company's first multi-faceted solution to growing with the constant change of the business environment. Business analysts link a company's technology and objectives, assisting in the process of turning data into revenue at a more efficient pace than a company without a business analyst. Business analytics solutions can be expensive, so it is helpful if your company has a reliable business intelligence software as well.
One of the core skills of a business analyst is actually management. With the ability to manage, along with the other skills necessary of a business analyst, there is only success to follow.
Some other necessary skills of a business analyst include: communication, technical skills, analytics, problem solving, decision making, and negotiation and persuasion skills.
A business analyst has many goals, the main ones being: meeting deadlines, cost controlling, and ensuring the proper implementation of a solution to a problem.
A qualified business analyst should have a degree in a related field, such as information technology, since business analyst programs are not widely available. They should also have passed the CBAP exam to be industrially recognized.
Business analysis is your company's key to making better business decisions, faster. After all, time is money. If top companies are utilizing business analysis and finding success in the usage, shouldn't your company be using it too?
Microsoft implemented a collaborative approach among their analytics team of 1,200 by shifting their employees into fewer buildings. This resulted in a 46% decrease in travel time for meetings, therefore giving the team more time to work on the important stuff: analyzing.
Uber created its Customer Obsession Ticket in 2018, which is a business analytics tool that uses machine learning to improve speed and accuracy when responding to support tickets. This has resulted in a 7% reduction in the time it takes to respond to support tickets, and thus better customer satisfaction.
What can your company increase speed on, resulting in better customer satisfaction and therefore better revenue for your company?
The Data Analyst Perspective:
Any business is also bound to come across data and statistics. Knowing how to utilize those numbers will make or break a company. As artificial intelligence grows in capability and popularity, it might seem like a great option, however AI often combines statistics, analytics, and machine learning into one subject. In reality, these are all very different and need to be analyzed separately. This is why using a machine won’t benefit your company as much as utilizing real people. So, your company's second multi-faceted solution to growing with constant change of the business environment is to hire a data analyst, perhaps even before anyone else.
Ask your data analyst to achieve the height of what they can in their specific area of expertise, whether it be statistics, analytics, or machine learning, and then focus on the other two areas. After all, being an expert in one and mediocre in the other two will be more beneficial than being merely mediocre in all three.
According to research done by Trilogy Education, the five most important qualities for a data analyst to have are: data analysis, SQL, data management, business intelligence, and data warehousing.
Data analytics is a complicated job, so let's face it, much of the time an initial attempt can be improved upon. Some main road blocks for data analysts include culture, structure, and approaches to problem solving. Analysts often fail at explaining the details to the decision maker of the company. After all, not everyone is well versed in data analytics. In a survey done by Kaggle, four out of the seven biggest road blocks of getting the full value out of a data analyst comes down to the last mile issues, and yes, this is very frustrating to both parties.
How can your company better utilize data analytics without the road blocks? The answer to that is to gather a small team of data analysts, with a chief analytics officer. Perhaps hire other employees to help with the transition of versing the decision makers on the information from the analysts. The work of the analysts is hard enough, so asking them to go through the steps of presenting it in a way that a non-analyst can understand is almost too much to ask. Companies need to think of data analytics as a multi-step process, hiring different people who can fulfill these different steps, and therefore bridge the gap between the analyzed data and the understanding of the data. The use of cloud storage may be beneficial as well, since it opens up optionality and makes all data easier to transfer into the data bank and access, without disrupting analysts and business applications in the process.
In between the Business and Data Analyst, the Systems Analyst needs to understand how to leverage and integrate these perspectives!
While data is the foundation of a business, harnessing it is challenging since some data is formless. Visible Systems took up that challenge by using The Universal Model Framework as a means of detecting patterns in data. Using The Universal Model Framework you are able to get a head start on your data modeling efforts and you don’t need to re-invent the wheel each time your business introduces a new system. This can help you save a lot of time and effort that can then be re-utilized in other productive endeavors.
Modeling data when needing to aggregate data across multiple data sources:
Even though most data modeling efforts are data modeling constructs that have been created numerous times before, doing so can be a challenge. Additionally, though many applications are supported from single data source, decision support processes may require additional data sources especially for solving problems that require hybrid, multi-faceted solutions. By showing interdependencies, The Universal Model Framework enables us to easily aggregate data across multiple data sources.
The Universal Model Framework enables:
- Grouping activities according to subject areas and business function before designing architectural road maps, keeping your business strategy in mind. This allows us to determine the business objects and functions necessary to achieve the intended goals.
- Examining changing requirements and what they can do for existing business processes, design, and development.
- Collaborating with key decision makers and providing consistent support for applications, data requirements, and requests.
- Accumulating essential information into sound business terms that stakeholders, employees, and management can understand and utilize.
You can think of the Universal Model Framework as a large ontology from which taxonomies are derived for a better understanding of your business domain. Each entity, when viewed within the context of a taxonomy represents a cohesive business intel. Henceforth, data can be viewed from a number of different perspectives and when instantiated can be queried and viewed as they are in a specific moment. For instance, an entity that is viewed from a sales perspective will have different business intel when it is viewed from, say, a production perspective.
The Universal Model Framework brings these perspectives together in a comprehensive, meaningful way. In some ways, it is the sum of the parts of your business that have hidden potential which can be tapped into via different perspectives.
Rethinking Data Discovery
While organizations may go through some growing pains, customer dissatisfaction can derail even the best laid plans. Forecasting business and operational needs on the basis of irregular and unreliable information can have costly repercussions. If the analytical tools you have are not producing results that can help you make personalized decisions, it might be time to rethink data discovery.
With both internal and external influences, the data you seek may seem abstract. Today, enterprises need agile data discovery platforms that can take diverse information into account along with variables that can be used in models. At Visible Systems Corp, we can help you harness the data you need in a rapidly evolving business environment to gain a competitive advantage.
Here are just some ways we can make a difference for your enterprise:
Recognizing Patterns in Existing Data
Looking for searchable solutions in a pile of unstructured data is like looking for a needle in a haystack. Our technicians are trained to spot hidden trends and patterns in that tangled web. Through this process, we will gather, catalogue, annotate, and combine it into an understandable and user-friendly format to streamline critical decisions. This allows us to create results that unlock actionable insights for business growth.
Saving Time and Resources
At Visible Systems Corp, we understand that traditional data analysis tools are only designed to analyze data that is in a specific format. However, most data is formless since it is sourced from different locations. Using data discovery, we can aggregate and format it from various sources to streamline analysis. This results in data that is in the right format, which can ensure timely deliverables.
We realize that data discovery is a continuous process and old data is as valuable as fresh data. That is why as it is accumulated, we clean and store the existing data besides ensuring that it remains available for future use.
Streamlined Data Modeling
Unlike outdated data analysis models, with our data discovery we model your business data using an understandable structure. This includes harmonizing disparate sources to ensure a uniformity that can make streamlined data analysis possible. This affects businesses directly unlike their predecessors that involved the processing of huge amounts of data for actionable results.
Read more about how a "unified" perspective of the Enterprise plays a key role in understanding change and see the article published by the Harvard Business Review on "The Business Case for Curiosity".