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Challenges Of Advanced Data Analysis In Companies

Data Analysis: Although 71% of global companies want to invest in business analytics, according to MicroStrategy research, the challenges for its implementation are significant and multidisciplinary.

Knowing that the BA is much more focused on predicting trends and behaviors, it is already to be expected a great complexity of the operation. After all, although it represents immense power to the organization, the task of getting the forecasts right is complex.

We list below some of the main alert points for the use of BA:

#1. Large-Volume Data Processing And Handling

Big Data ties in strongly with business analytics. This is because there is a need to manage a massive volume of information representing precise action directions.

On the other hand, the process of collecting, organizing, and interpreting data is a complex one. A survey released by Business Wire showed that 99% of 1,000 respondents said they invested in Big Data, and only 24% created a data-driven organization.

The complexity of the process of implementation and data processing can justify this. It is worth remembering that although a high volume of data allows for more accurate insights, managing this volume is much more complex.

Therefore, the need to invest in data management is extreme in Business Analytics. Thus, in addition to adopting a sound system, the organization must remember to invest in innovations to handle ever-increasing volumes of data.

In short, the company must be prepared for the high collection and have reasonable investigations to correctly implement the BA in its culture.

#2. Complex Data Modeling

The diversity of sources and data types in the analysis represents the need for a data scientist for assessments.

This is because choosing important indicators and information from reliable sources is essential to make informed decisions. On the other hand, even because of the large volume, this task becomes a significant challenge for companies.

#3. Technological Infrastructure

The change and updating of tools are constant nowadays. Therefore, always having the best applications for data analysis is a task that requires continuous monitoring.

On the one hand, the widespread need for updates in the technological structure is good, as it enables increasingly accurate and simplified assessments. Even so, changing the infrastructure becomes a significant challenge for managers.

Resources And Solutions To Support Quantitative Analysis

To carry out the steps, it is evident the need for tools that allow, for example:

  • Collection of data from different sources;
  • Data evaluation and visualization;
  • Modeling of the extracted information;
  • Manufacture models that are visually easy to interpret.

For this, the company can count on several solutions, which is why business analytics is associated with technology.

Highly accurate predictive analyses can only be made possible with up-to-date and appropriate tools for each step.

Still, don’t worry. Although it involves complex steps, the process can be done using solutions found on the market. Below, check out some of them:

OLAP (Online Analytical Processing) System

An OLAP system strongly assists the analyst in the initial stages of Business Analytics. These applications’ interfaces allow the professional to compare and visualize the data differently.

Thus, it is much simpler to compare trends to identify the most recurrent employee behavior. To exemplify this advantageous analysis for the HR sector, consider the following:

  1. Luiza is a manager who needs to identify the average adaptation period for professionals.
  2. For this, data documenting the productivity of newly arrived professionals in the last three years were collected.
  3. An OLAP system allows the analyst to compare professionals from different sectors, different levels of experience, and backgrounds;
  4. Thus, Luiza not only identifies the average time for professionals to adapt but can also see in the generated report which sector promotes a faster adaptation;
  5. Therefore, the manager’s action involves comparing the reception of the sectors, which leads her to develop a standard onboarding strategy that promotes a shorter adaptation time in all the other sectors.

Without a different view of data, the manager could have much more difficulty identifying the causes of the faster adaptation, comparing it with the employee’s experience level only.

On the other hand, with the different analysis perspectives provided by this system, the analyst can offer a greater volume of insights.

Data Visualization

Data visualization is the solution that promotes documents with visual elements. Consequently, the organization’s decision-makers understand the data collected and perform faster and more accurate visual analysis. It is an essential resource for the final stage of Business Analytics.

The tool that generates and organizes the data for the visualization can include graphs, colorings, maps, interactivity, and several other features.

Although the BA process is highly complex and sophisticated, the representations must be simple. To group the extracted information and make it easily interpretable, it is essential to have a specific technology for this.

Business Intelligence Solutions

It is only possible to develop a forecast of behaviors and trends by assessing the organization’s current scenario.

Therefore, the initial step for companies that want to implement Business Analytics is to use a BI system. The solutions allow the structuring of metrics systems that will be explored later by BA.

Therefore, a Business Intelligence system can consolidate the use of advanced analysis resources that Business Analytics promotes.

Also Read: How Artificial Neural Networks Dictate New Technologies

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