Introduction to Data Warehousing: Building a Cutting Edge Data & Analytics Strategy
If you have ever worked or are working in a data-driven organization, you must have come across the fact that large volumes of data are generated on a day-by-day basis. This data needs to be integrated and stored in a shared platform, from where different departments across an organization can use it for business intelligence, analytics, reporting, and decision-making purposes.
We live in a world where technology has overtaken most of the organizational processes, including data integration, and more tools and technologies are going to be introduced in the future to take care of our growing data needs.
The changing face of data
Unlike earlier days, data comes in various forms and from different platforms or sources. The data needs to be precisely integrated into a common platform, known as a data warehouse, where it can be transformed to drive meaningful information. All big data organizations have incorporated the best data integration tools and are working with platforms like DataChannel to drive useful insights from the big data silos.
Now, it has become quite easier to consolidate data from disparate systems, before finding a pattern out of it. But before diving deeper into the concept, one should first know what Data Warehousing is.
What is Data Warehousing?
Data warehousing is a process used to collect and manage data from multiple sources to drive valuable business insights. It helps you bring all your data under one roof so that the same can be utilized to perform analysis and to report at different aggregate levels.
It is the core of the BI system and helps you make better business decisions. In simple words, it is the electronic storage space for all your business data integrated from different marketing and other sources.
DataChannel offers you a cloud-based data warehouse platform, where you can securely integrate the data from several sources and bring them under one big umbrella and transform it into valuable insights that will help your business become the leading one in its respective niche.
The platform is equipped with tried and tested pre-built models that sync all your historical and present data and allow you to monitor your business operations effectively.
Types of Data Warehousing
There are mainly three types of data warehousing, and that is as follows:
- Enterprise Data Warehouse: Enterprise data warehouse is a centralized warehouse that offers a decision making support to different departments across an enterprise. It provides a unified approach for organizing as well as representing data. With this warehouse at your end, you gain the ability to classify the data as per the subject and grant the level of access to different departments accordingly.
- Operational Data Store: Popularly known as ODS, Operational Data Store is used when an organization’s reporting needs are not satisfied by a data warehouse or an OLTP system. In ODS, a data warehouse can be refreshed in real-time, making it best for routine activities like storing employees’ records.
- Data Mart: As part of a data warehouse, Data Mart is particularly designed for a specific business line like finance, accounts, sales, purchases, or inventory. The warehouse allows you to collect data directly from the sources.
How Data Warehousing Works?
The architecture of a data warehouse consists of three tiers. The bottom one is the database server, where data is loaded and stored. The middle one is the analytics engine that analyzes the data.
The top one is the front-end client that represents the result through analysis, reporting, and data mining tools. The entire working of a data warehouse depends on these tiers.
The Data warehouse works by collecting and organizing data into a comprehensive database. When all the data from multiple sources is collected, then it is sorted into various tables depending on the data type and layout.
You can even store your confidential business details in the data warehouse, like employee details, salary information, and others.
Information derived from a data warehouse helps companies to analyze their customers and anticipate the coming trends in the competitive market. By having precise information about what their customers want and what they are expecting from a business, it becomes easier to serve them right and achieve an optimum level of customer satisfaction.
With the right data warehousing platform, you can always think ahead of your competitors when it comes to historical analysis, product development, pricing strategy, forecasting market changes, and customer satisfaction. Investing in an efficient data warehouse will help your business climb to the top of the competition curve.
Data Warehousing and Data Analytics
People often get confused between data warehousing and data analytics. The two terms are similar, but not the same, and that sums up the entire difference between them. Data warehousing is the process of consolidating all the organizational data into one common database.
On the other hand, data analytics is all about analyzing the raw data and driving conclusions from the information gained. The concepts are interrelated but different. The process of data analytics begins once the process of data warehousing has taken place.
General stages of Data Warehouse
The need for a data warehouse has grown with time. Now, every organization, irrespective of its size, wants a data warehouse that can help it get a unified view of all its data. This is the time when the sophisticated use of a data warehouse began.
Here is the list of general stages of the use of a data warehouse:
Offline Operational Database: In this stage, data is copied to a server from an operating system so that loading, processing, and reporting the data does not impact the performance of the operational system.
Offline Data Warehouse: The data stored in the warehouse is regularly updated from the operational database to derive useful business insights.
Real-time Data Warehouse: Whenever a transaction takes place in the operational database, the same is updated in the data warehouse.
Integrated Data Warehouse: Every transaction taking place in the operational database is updated simultaneously in the data warehouse. Then, the warehouse generates transactions that are forwarded to the operational database.
Data Warehouse Appliances
Data Warehouse Appliances are a set of hardware and software tools used for storing data. Every data-driven business makes use of these appliances for building a centralized and comprehensive data warehouse, where all kinds of functional business data can be stored.
When these appliances are combined with data warehouses, help organizations to meet their modern-day data integration requirements. By combining all customer data in a data warehouse, you can get the following benefits:
Easy access to customers’ historical data.
Enhanced interactive voice response technology
Customized digital communications
Data Warehouse appliances act as the building blocks for creating efficient business data warehouse systems.
Concepts of Data Warehouse
- Basic Data Warehouse:
With a basic data warehouse, you can minimize the total amount of data stored in a system. The minimization of data is done by removing redundancy within the information, making it look easy and clear.
As the concept combines information from multiple sources, different departments in an organization can access data directly from the warehouse, without wasting any time opening multiple folders to get the relevant information.
- Data Warehouse with Staging Area:
Some data warehouses perform the cleansing process before moving the data to storage. These systems have “staging areas” where information is first reviewed and evaluated and then transferred into the warehouse. This will assist you in getting only useful and relevant data stored in your warehouse.
As a business, you can use data warehouses with staging areas to process large volumes of customer data so that irrelevant information can be filtered out, and your team will only be left with precise information to work on.
- Data Warehouse With Data Marts:
With data marts, you can enhance your data warehouse’s customization level. Once the data is processed, data marts streamline information to teams and employees who need it the most. This will help different departments across an organization to boost their productivity as they don’t have to wait for other departments to share the required information.
This will also increase the pace of decision making and assist businesses never to miss a growth opportunity.
Data Warehousing and Business Intelligence
If you have reached this part of the article, then you must have developed an understanding of what data warehousing is. Still, to sum up, data warehousing is a process of combining data from multiple sources and organizing it in a way that supports organizational tactical and strategic decision making. The main purpose of a data warehouse is to provide a transparent picture of the business at a given point in time.
On the other hand, Business Intelligence (BI) can be described as a set of tools and methods that facilitates the transformation of raw data into meaningful patterns to drive useful insights that can be further used for making better business decisions. The process of BI involves data preparation, analytics, and visualization.
All the BI tools do not aim to provide all the three capabilities, therefore you can go for full-stack solutions where you can receive the perks of all three capabilities.
To work with unstructured data, BI tools need a data warehouse as they have limited data preparation capability. However, you can get a full-stack Business Intelligence Analytics & Dashboard Software from DataChannel that provides you an end-to-end data warehousing solution.
Business Intelligence is an umbrella term used with data analytics. It is a process that performs data preparation, analytics, and visualization. Whereas, data warehousing describes tools that combine data from disparate sources, clean the data, and prepare it for analysis.
Here, we are listing some of the BI tools that can help you get a more straightforward approach to analyze and present data sets in a form that helps users to easily draw conclusions.
Tableau is one of the fastest-growing data visualization tools used by big data-driven organizations for BI purposes. It simplifies raw data and converts the same into an easily understandable format. With this tool at your end, you can speed up the process of data analytics. The tool creates visualizations in the form of worksheets and dashboards that can be understood by every professional working in an organization. The tool allows even a non-technical person to create a customized dashboard.
Looker is a cloud-based business intelligence platform that collects data from multiple sources to provide its unified view that helps users to make better business decisions. The tool allows the different departments across your organization to analyze supply chains, interpret customer behavior, quantify customer value, and evaluate distribution processes more efficiently. It’s easy to use dashboards that allow users to present data and insights into customized graphs, charts, and reports.
- Power BI:
Another business intelligence platform by Microsoft that pulls data from several source systems in the cloud and on-premises and sums the information in an easy-to-understand dashboard. The platform can be integrated with other Microsoft platforms like Excel and help users to go beyond bar and pie charts.
A powerful BI tool that allows both data analysts and non-technical users to visualize and analyze data from multiple data sources quickly. It has data connectors that you can use to integrate all common data sources in seconds. With over 80 predefined dashboard templates and drag & drop user interface, you can build amazing data visualizations within minutes. The platform has many other features that add another level of efficiency to your data visualization and data analytics process.
- Zoho Analytics:
Zoho Analytics is a highly reliable BI and data analytics software that helps you find hidden insights from raw data and allow you to create visually appealing data visualizations and insightful dashboards within minutes. With this tool, you can sync all your data residing in different flat files, cloud storage, databases, and systems to perform in-depth reporting and analysis to make better decisions based on informed business insights.
How does DataChannel help you achieve your data objectives?
DataChannel is among the leading organizations when it comes to database services and products. It offers a cloud-based data warehousing solution that consolidates all your data from various source systems and platforms under one roof, where the same is further analyzed and transformed into valuable business information.
If you want to sync all your historical and present data in a common space to see where your business is heading, then DataChannel data warehousing software has your back.
With us, you gain the ability to customize your data warehouse in a way that it exactly meets your data integration requirements. With such a customization level, you can create a scalable and future proof system architecture to handle any volume of data without any manual help.
At DataChannel, we have hundreds of pre-built connectors that allow you to integrate your data residing in multiple data sources and cloud apps. Still, if you have any specific requirements not available on our existing list, we can build it for you. With our data warehousing solution, managing even the complex data pipelines becomes easier. You are no longer going to need data specialists to manage your data as our easy-to-understand interface will be at your service.
DataChannel helps you to turn your data into actionable insights, along with securing it from unauthorized access. With over 100+ API connectors, we help you collect your data from multiple marketing platforms that assist you to boost the sales of your products and services.
Here are some of our popular API connectors:
- Google Ads:
The Google Ads API Connector helps developers build applications that can interact directly with the Google Ads Server. With this connector, you can have a big picture of your marketing and sales data that will help you manage your Google Ads Campaigns with ease.
- Google Analytics:
The API allows you to access report data in Google Analytics easily. With data integration to Google Analytics, you can perform ROI analysis and measure your campaigns’ performance to find which campaign is bringing you more returns. The API helps in saving both time and effort.
- Facebook Ads:
The API allows your developers to build applications that help you to market your products on one of the most used social media platforms – Facebook. It integrates your Facebook Ads data, along with providing secure access to several fragmented Facebook Ads statics.
- Facebook Insights:
Data Integration to Facebook Insights allow you to monitor your brand performance on one of the biggest social media platforms. It also provides a view of all your past and present reports and customer engagement statistics.
Salesforce API data integration frees you from the manual task of data, which, in turn, eliminates the risk of errors. You can connect your Salesforce to a multitude of different solutions for providing several benefits to your sales team.
- LinkedIn Ads:
With Linkedin Ads Data Integration, you can analyze your advertisement data to boost the pace of your advertisement productivity, and develop better marketing solutions.
The connectors can be used with BI tools like Zoho Analytics, Tableau, Looker, and others to see and understand your marketing and advertising data clearly. You can combine your data with smart dashboards and efficiently track the performance of your marketing and ads campaign, along with sharing reports at a thundering speed.
The much-needed Cloud Data Warehouse
As we are coming towards the end of the topic, we cannot leave to discuss one of the much-needed data warehousing solutions – Cloud Storage. A cloud data warehouse is a critical part of any data-driven organization, where it can store any amount of data and the computing power required to process the data.
The growing needs of data were becoming a little to cater, with the limited features of an on-premise data warehouse. Whereas a cloud data warehouse can easily be scaled according to business data needs, along with keeping your data secure from unauthorized access.
DataChannel provides data warehousing solutions that are designed to work with any cloud service provider. We have made use of cloud-native architecture that allowed us to offer a very reliable and scalable architecture at cost-effective prices.
Here are some other widely used Cloud Data Storage Solutions:
- Microsoft SQL Azure:
Microsoft Azure SQL is a scalable, reliable, and intelligent database service built for the cloud. It is backed with AI technology and automated features that keep the solution up-to-date. The database frees you from configuring and managing large backups and optimizing the performance with the help of a SQL database.
Serverless compute, and Hyperscale storage instantly adapts to the scaling requirements of your business. With this cloud storage solution at your end, you can drive all your attention towards building new applications without stressing about resource management or storage size.
- Google Bigquery:
Google Bigquery is a highly scalable and serverless cloud data warehouse that helps you turn your raw data into actionable insights. The solution allows you to analyze petabytes of data at flash speed and share the excessive load of data scientists and data analysts. The SaaS platform is a cost-effective solution with built-in machine learning capabilities.
- Amazon Web Services (AWS):
Amazon Web Services is a cloud services platform that allows you to secure all your files on the cloud so that you can use the same whenever and wherever required. With this platform, you can run multiple applications and web servers in the cloud for hosting dynamic websites. The platform allows you to send emails to thousands of customers at a single click and send files around the globe to any person using a content delivery network.
- AWS Redshift:
Amazon Redshift is a well-managed, petabyte-scale data warehouse service in the cloud. The solution allows you to make the most of your raw data to acquire new and valuable insights for your business and customers. When it comes to
getting new insights from large data sets, nothing can match the efficiency level of AWS Redshift. It is a secured cloud service platform with excellent functionalities that help your business grow.
Today’s data-driven business world is quite competitive, and to survive and grow, you must have access to the right data integration platform. In every organization, large amounts of data are generated daily, and the organization that does not use such information fails to sustain in the market.
That is when the role of the data warehouse comes into the picture. A data warehouse is one of the most crucial elements that every business must-have in the present era.
A data warehouse will help you combine data from various sources into a format that can easily be understood by employees working in different departments of your organization. Having the right information will help the authorized personnel make critical decisions at the right time so that your business can meet its goals more effectively.
A data warehouse is essential for any business that wants to scale its business operations and become a renowned name in the data-driven marketing landscape. If you are also looking to implement a data warehouse into your business operating systems, reach out to us through our website