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Over the last decade, the need to interpret and analyze big data has resulted in serious growth for businesses across the world. With the help of digital products and solutions, industries are collecting vast amounts of digital data that not only is a huge asset for them, but also opens the door for them towards several new opportunities. Attaining operational efficiency, product innovation, and delivering a unique customer experience can be some examples of such opportunities.
However, as exciting as it sounds like, the road to reaching this point of efficient data management is not an easy one. To derive suitable insights from these huge chunks of data requires a rigorous and on-going process of gathering, converting, uploading and applying business intelligence and analytics over this data.
What Is A Data Warehouse?
As the name implies, a data warehouse is a centralized location that enables you to store and manage all your business data. A data warehouse can either be hosted on-site/on-premise or be cloud-based. Since every business is different, the choice to go on-premise or to the cloud is open to suit the business dynamics and aspects. There are advantages and disadvantages for both; Cloud data warehouses offer scalability at a comparatively lower upfront investment, whereas the level of security is much greater in the case of an on-premise data warehouse.
However, below are some of the aspects that are encouraging businesses to move to a Cloud Data warehouse:
With the need to expand the storage capacity, it will be imperative for an on-premise DWH to configure additional storage hardware. However, with a Cloud data warehouse, the storage capacity can be either scaled up or down as per the business needs, with no specific need to make any configuration changes. Thus, making it a highly scalable option.
There is a major cost involved to set up an on-premise infrastructure, a Cloud data warehouse eliminates the up-front investment to a great extent. Also, businesses only pay for the resources that they use, that further improves operational efficiency.
Data warehouses fetch data from several siloed systems. With a cloud based DWH, it's easier to connect to other cloud services, enabling a seamless data transfer.
A cloud-based DWH is comparatively faster than an on-premise one, mainly due to the use of ELT (extracting, loading, and transforming) — which is not common for on-premise solutions.
How can Business Intelligence combined with Data warehousing improve decision-making?
Gartner defines Business intelligence as “an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.”
Although Business intelligence and Data warehousing operate in the same space and have a lot in common (both are involved in the storage of data), Business intelligence serves as the next step for an efficient data warehousing process, i.e. to collect, analyze, and present key business information for the management. BI tools such as Power BI and Tableau have been two of the biggest players in the market in recent years and are leveraged by enterprises on a global level.
An efficient BI&DW practice can help derive strategic decision-making, such as follows:
Data discovery, simply put, is a process to extract meaningful information from a larger set of raw data. The information extracted can be analyzed to find patterns and correlations, to eventually predict outcomes. An efficient data mining process can help you improve operations, cut down costs, increase revenue, and more.
While metrics are used to analyze the overall performance of a business, performance metrics are the results delivered from such an analysis, which is analyzed further to determine the trends within a performance range. This eventually helps to formulate key business strategies.
Statistical analysis involves gathering and analyzing data samples. In this case, samples can be termed as a small section of data extracted from the huge amount of data. This helps in streamlining the BI&DW process through micro analysis, which further helps in making smarter business decisions.
Intuitive Data Visualization
Data visualization simply helps in analyzing the data and visually demonstrating the key aspects of the analysis to help businesses make better informed decisions. Visualizations can be in the form of charts, infographics, depicting numerical and graphical representations. Most organizations still follow the traditional method of presentations over excel spreadsheets, which can become cumbersome at times. Data visualization on the other hand, provides a much more effective and intuitive way for an organization to access useful information from its data.
An effective BI&DW practice helps businesses create queries to check the accuracy of the data. This helps in having the right data at the right place, to get meaningful, quality information as and when needed.
Aress’ BI service uses popular Data visualization tools like Tableau and Microsoft Power BI to deliver user-friendly reports, dashboards and intuitive intelligence from complex organizational data. Through a combination of experienced BI Professionals and a Centre of Excellence (DW/BI CoE), Aress is well equipped to deliver success to organizations across multiple domains like Banking and non-Banking Finance, Insurance, Healthcare, Lifesciences, Manufacturing, Retail & Logistics.
We also partner with top Business intelligence and Data warehouse technology vendors to ensure that our customers get the BI&DW solution that best fits their needs. We collaborate with our customers to develop a BI&DW roadmap that delivers short-term, tactical, quick wins, as well as strategic successes during the long term. With the boom of big data and advanced data technologies, analyzing business data gathered from every possible source helps organizations find opportunities to grow and improve their products and services.
Category: Data Analytics, RPA & AI