Author: GURU Solutions
Friday, November 18, 2022

How you can Improve Database and Analytics Performance

It would be best if you had tips to improve your database and analytics at your fingertips, whether you are a small or big business. But if you don't know them yet, don't worry! This article will be the ultimate guide to learning tips on improving your database and analytics. I will encourage you to keep reading.   

There are several tips on improving your database and analytics; optimize queries, improve indexes, data defragmentation, increase memory, strengthen your CPU, and review access. Additionally, design your servers, ensure your server can handle the intended workload, use the latest version of your server and CPU, and research.  

Read on to learn more about the steps involved in data analysis. 

How you can Improve Database and Analytics Performance

Databases are at the center of every business application as they help collect, store and retrieve large amounts of data. As databases collect data, it transmits information and facilitates other business processes. 
It can be infuriating when the database performance is slow.

How you can Improve Database and Analytics Performance

Here are steps you can follow to improve database and analytical performance. 

1. Optimize Queries

Optimizing queries help in database improvement; insufficient questions can cause poor database performance. It would be best if you start by targeting specific queries. The efficient way of optimizing queries is using a database performance analysis solution to guide your optimization. 

2. Improve Indexes

Indexes can increase database performance by optimizing the query execution duration. Indexing is responsible for organizing all your data, making it easy to locate. The index makes a data structure that keeps all data collected, making it easier to find data and increasing the efficiency of data retrieval. Indexing increases database performance by speeding up the process. 

3. Data Defragmentation

As you write to and delete from your database, your data becomes fragmented, thus slowing down the data retrieval process. Fragmentation affects the query's ability to locate the information it is searching for quickly. 
Data defragmentation improves your database and analytical performance by grouping relevant data in one file and erasing index page issues. 

How you can Improve Database and Analytics Performance

4. Increase Memory

Enough memory enables the database to work effectively. You should ensure you have enough memory by checking your system's many page faults. If the number of defects is high, your host runs low or is out of memory space. By increasing your memory, you will boost your database performance and efficiency.

5. Strengthen Your CPU

It would be best to upgrade to a higher-class CPU unit to avoid database-related issues. The stronger your CPU is, the less struggle you will have when dealing with multiple requests and applications. To confirm whether your CPU is strong enough, you should check your CPU performance, including the CPU ready times, which indicates the number of times your system tried to use the CPU but could not because the resources were in use. 

6. Review Access

You will need to access what applications are accessing your database frequently. Review access will let you know if the problem is poor database performance or if just one client is experiencing problems. Trace what application is having an issue and solve it rather than wasting time redesigning the whole database when only one or few applications are having an issue. 

What are the Steps in Database Analysis

How you can Improve Database and Analytics Performance

Data analysis follows a step-by-step process to ensure efficiency. Each step requires a particular skill to handle it. 
We will analyze the data analysis process. Below are the steps you should take;

1. Defining the Question

The first step you should take is to outline and define your objectives and what you hope to achieve at the end of the process. By specifying your goals, you will have to develop a hypothesis and know how to test it and the proper tools. Alternatively, you can hire a data analyst whose main work will be to understand your business in-depth, define your goals and define your business problem easily. After determining your business problem, the data analyst can develop a proper diagnosis.

2. Data Collection

After outlining your goals and objectives, you can start collecting the appropriate data. Under this step, you must determine what data type you need and what you can discard to speed up the process. Data will fit into three categories, as shown in the table below;

The First Party Data The first-party data is data that you have directly collected from your customers. The data can come from transactional tracking data, your company's customer relationship management information, surveys, interviews, or direct observation.
Second Party Data

A secondary data source might be available from the company, or you can source it through a private marketplace. The second-party data is usually well-structured and reliable.

Third-Party Data

Third-party data is collected from different sources by a third party. Third-party data contains unstructured data that companies use for research. 

3. Cleaning Data

Once you have collected data, you will have to analyze it, which is cleaning the collected data. Data cleaning includes the following;

  • Erasing duplicates and errors
  • Making a structured data
  • Filling the major gaps
  • Data cleaning is essential for any business organization, as focusing on the wrong data will affect your results and consume much of your time. 

4. Do a Data Analysis

After cleaning your data, you will have to analyze it. Data analysis will largely depend on your goals and objectives. Here are the types of data analysis;

  • The descriptive analysis identifies what has already happened.
  • Diagnostic analysis that aims at understanding why something occurred
  • The predictive analysis aids you in knowing the future trends in the market by using historical data.
  • Prescriptive analysis  that helps in making future recommendations

5. Sharing Results

After the analysis, you can share your results and interpretation with your stakeholders. Your understanding determines the direction your company will go. 

6. Accept your Mistakes

The last step is to accept your failures, learn from them and improve on what you can. You can also list the predicted mistakes and follow up on what is important. 

What are the Takeaway Tips in Database and Analytics

How you can Improve Database and Analytics Performance

It would be best if you considered building, deploying, and configuring the Server hosting your database applications to increase its efficacy. Before deploying a new server, ensure you understand and know what type of Server fits your database issues.

Understanding your database issues will help you find the most suitable Server. Additionally, you should also understand your configuration issues before making any changes. Knowing the problem will help you give the correct diagnosis instead of solving what you don't know.

You should stress test your hardware to ensure that your Server can handle the work you intend to do. The testing will help you know the limit of your Server. You should also deploy database performance software to monitor your servers and alert you when a problem arises. 

Updating your servers and operating system is essential to every business. Your business needs the latest version of any software for your database to work seamlessly. 

You can learn how to improve your database and analytical performance through research. You can also get more knowledge from other business people. 


Database and analytical performance is a crucial part of any business. You should endeavor to improve your database analysis for it to work effectively. The above steps will guide you on improving your database analysis and the process you should take. Guru solutions are expert in database & analytics services. 

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