Data Analysis

Business data analysis includes the activities to help managers make
strategic decisions, achieve major goals and solve complex problems.

What is Data Analysis?

The process of evaluating data  using  analytical  and  logical  reasoning  to  examine  each component of the data provided. This form of analysis is just  one  of  the  many  steps  that must be completed when conducting a research experiment. Data  from  various  sources is gathered, reviewed, and then analyzed to form  some  sort  of  finding  or conclusion. There are  a  variety  of  specific  data  analysis method, some  of  which include data mining, text analytics, business intelligence, and data visualizations.

Data  Analysis  is  described as the process of bringing order, structure and meaning to the mass of collected data. It is considered as messy, ambiguous and time-consuming, but also as a creative and fascinating process.

The term data analysis  has  long  been  synonymous  with the term statistics, but in today’s world, with massive amounts of data available in business  and  many  other  fields  such as health  and  science, data  analysis  goes  beyond  the  more  narrowly  focused area of the traditional statistics.

Business data analysis comprises the activities to  help managers make strategic decisions, achieve major goals and solve complex problems, by collecting, analyzing and reporting the most useful information relevant to managers' needs. Information could be about the cause of the current situation, the most likely trends to occur, and what should be done as a result.

Activities can include identifying and verifying potential strategies and solutions, and testing the feasibility of  the  most  favored  solutions. Analysis  is  based, a s much as possible, on relevant, accurate and reliable information, often involving interactive  automated statistical analysis -- or data analysis.

Why Data Analysis?

With today’s technology, companies  are  able  to  collect  tremendous amounts of data with relative ease. Indeed, many companies now have more data than  they  can handle. Data is usually  meaningless  until  they  are  analyzed for trends, patterns, relationships, and other useful information.

In many business contexts, data  analysis  is  only the first step in the solution of a problem. Acting on the solution  and  the  information it provides to  make good  decisions is a critical next step. Therefore, there  is  much  care  on analytical methods that are useful in decision making. The methods  vary  considerably, but  the  objective  is  always the same—to equip you with  decision-making tools that you can apply in your company.

Data Analysis or Data Analytics?

Data analysis and data analytics are often treated as interchangeable terms, but  they hold slightly  different  meanings. Data  analysis  is  the  overarching  Data Analyst  practice  that encompasses the use of data analytics tools and techniques to achieve business objectives.

Data analysis is a broader term that refers to the  process of  compiling and  analysing data in order to present findings to management to help  inform business decision making. Data analytics is a subcomponent of data  analysis  that  involves the  use of  technical tools and data analysis techniques.

Data analytics is the  science of  drawing  insights  from  raw  information  sources. Many of the techniques and processes  of  data  analytics  have  been  automated  into  mechanical processes and algorithms that work over raw data for human consumption.

Data analytics techniques can reveal trends and metrics that would otherwise be  lost in the mass of information. This information  can then be used to optimize  processes to increase the overall efficiency of a business or system.

Data analytics is broken down into four basic types.
 

• Descriptive analytics describes what has happened over a given period of time. Have the number of views gone up? Are sales stronger this month than last?
• Diagnostic analytics focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?
• Predictive analytics moves to what is likely going to happen in the near term.  What happened to sales last time we had a hot summer? How many weather models predict a hot summer this year?
• Prescriptive analytics moves into the territory of suggesting a course of action. If the likelihood of a hot summer as measured as an average of these five weather models is above 58%, then we should add an evening shift to the brewery and rent an additional tank to increase output.

Priority for Enterprises

The problem of understanding the behavior of information systems, and the processes and services  they  support  has  become  a  priority in  medium  and  large  enterprises. This is demonstrated by the  proliferation  of  tools  for  the analysis of process  executions, system interactions, and  system  dependencies, and  by  recent  research works  in  process  data warehousing and process discovery.

The adoption of business process intelligence (BI) techniques for  process  improvement  is the primary concern for larger companies. In this context, identifying  business  needs  and determining solutions to business problems requires the analysis of  business process data.

Analysis of business data  will help to discover  useful  information, suggesting conclusions, and  supporting  decision  making  for enterprises, and enable process analyst to answer a huge and different amount of questions.

Contact  Solver Corporate to help your company explore Data Analysis  Solutions.