HOW TO BUILD A Cost Effective DATA WAREHOUSE in 2019

 

 

Why businesses need big data?

 

 Businesses and organizations are built with the same come purpose in mind i.e. to ensure profit maximization. Keeping track of each item available in the inventory to the recent sales figures, these companies want everything single thing to be kept recorded and later utilized in the most efficient way whenever needed. This accumulation of huge data from everyday transactional to managing activities takes the form of Big Data and now companies want a fast, quick and efficient way to manage their big data using the latest BI tools.

  

 

 

What is data warehousing?

 

One such technique is called Data warehousing which is considered to be a dream of every business analyst because it gives such tremendous power to analyze data within seconds and conclude extremely useful information from it to make intelligent business decisions. On the same concept, a data warehouse is a large storage area of big data, with data coming from a wide range of sources and is used to guide managing directors in critical decision making.

 

  

What points do I need to know about data warehousing before building my own data warehouse?

 

To improve corporate profits and overall business performances, Data warehouses are mostly used to associate big business data towards providing better executive insights. Data warehouses are greatly different from ordinary databases. Because the normal databases are mostly focused on updating the real-time data with a greater focus on achieving accuracy and precision, however, a data warehouse gives a long-range extensive view of the data over a period of time. This gives a big picture of the company’s overall performance in the last 5-10 years and which steps should be taken to improve those results.

 

  

Why companies face difficulty in building a data warehouse?

 

Data warehouse implementation techniques are highly technical and are not cost –effective. It requires a good budget and a flexible time schedule to implement otherwise it gets too chaotic with the company’s data gathering process. Another issue companies face is that data warehouses do not excel at unstructured or raw data. And because of the budget issue, it becomes almost a dream to implement a data warehouse for small businesses.

 

 

 

How long does it take to build a data warehouse?

 

If someone has hired expert data analysts and are following all the right, cost-effective and efficient techniques then it may take 6-8 weeks otherwise the process gets a little longer.

 

 

 

Data Warehouse Implementation Steps

Let us see what are some of the points that we need to keep in mind before building a cost-effective data warehouse in 2019:

 

1. Determining your own business objectives

The first step towards building a data warehouse from scratch includes a thorough understanding of the company’s goal, mission, vision, its future plans, its target audience, financial reports, qualitative and quantitative success determining factors, etc. All these points jointly give a better understanding of the business itself. Suppose the managers want to make a big decision about hiring the new employees for a certain product, now before they start doing the interview processes, they need to better analyze the overall business, whether this decision of hiring new people will be beneficial for the long run for this particular business or not, whether we should adapt technique A or go for technique B, each and every decision requires a complete in-depth understanding of the business model.

 

2. Gathering the information

Next step is to gather as much data as possible, because the bigger the data is the better predictions it gives for the future. You can collect information about some particular activity or idea by taking surveys, filling questionnaires, interviews, observations, you can also gather data from company’s financial reports, Customer relationship management solutions or other related tools, etc. All these mediums can prove extremely beneficial in gathering a sound, accurate and wide variety of useful information.

 

3. Analyzing the information

This is considered to be a big problem for data warehouse designers about how they analyze the information being gathered. To minimize any ambiguity in the prices, they need to be frequently in close connections with the people involved in the process, so they can understand the activities in detail and interpret the information rightly.

 

4. Identifying the core activities involved

By this point, you must have a very clear understanding of what your business is about. Now you have to identify the key performance indicators just like a total number of sales, revenue generated in the last 6 months, total employees hired, etc. In this phase you need to identify the core business activities involved in your organization, e.g you want to conduct training for the employees of a certain division, your business needs to hire a new employee or have launched a new product line, we need to identify the entities involved towards creating the key performance indicators.

 

5. Locating data sources

How to choose a data warehouse depends upon what you want from it to get done for you. Data warehouse designers work closely with the people involved in the business processes to gather accurate data which can help in giving accurate predictions towards future decisions. As discussed earlier, information can be gathered from sources like CRM tools, employee’s data records, surveys, questionnaires, etc. Now we have to all this information into a structured, detailed database format to be entered into the data warehouse. We need to move the data from these tools to the data warehouse in a systematic way to minimize any installation errors.

 

6. Implementing the plan

After developing the complete plan, now is the time to implement it. By estimating a proper timeline, setting the scope of the project we can start implementing the data structures into the system. Every new data structure will be added next to the previous one and will be connecting like the dots of a picture, and will keep on adding value to the system incrementally. Once done, our data warehouse is ready to help us toward guiding in critical decision making.