Is storing your data as important as processing your data?
“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.” – Aaron Levenstein
Efficiency gains of up to 90% is possible through the effort of structuring the data you collect and store. Deciding formats of data storage is the very first business decisions that indicates a data driven growth mindset within an organisation. No amount of data can prove worthless if it can be deciphered in the right manner. Hence gathering and storing of data is critical and crucial for analysis. Enterprises are constantly faced with this never ending quest for new and efficient ways to manage and store data. A careful analysis has to be made after consideration of cost, storage capacity and operational needs associated with each storage medium. Here are a few storage formats that we would like to talk to you about.
Data Lake – Wikipedia defines a data lake as a single store of all enterprise data including raw copies of source system data and transformed data used for tasks such as reporting, visualization, advanced analytics and machine learning. So that implies data in all its forms, both structured, unstructured and from different segments of the organisation are stored in a data lake and they are not necessarily organised and manipulated. Accessing information from a data lake requires special technical and inquiring skills and these can be accessed only with niche expertise. This makes it difficult to sort through and find relevant information from the vast pool of data waiting to be cracked. Data lake follows a centralised architecture and is one of the low-cost options in terms of data storage and is often referred to as a data dump.
Data warehouse – It is a central repository of information. It is a data storage system used for reporting and analysis. It is a process of collecting and managing data from varied sources to provide business insights. A data warehouse is used to collect and analyse data from heterogenous sources. It is the electronic storage of large amount of information designed for query and analysis than data processing. Unlike data lakes, data warehouse deals with only processed data, which offers advantages in terms of storage space and accessibility. It is considered a core element of Business Intelligence. The core difference is companies choose data warehouse over data lake when they need data to be ready and waiting for analysis. There are three types of data warehouses. Enterprise Data Warehouse, Operational Data Storage, Data Mart.
Data hubs – Theyfollow a hub and spoke architecture. Organised data from multiple sources can be categorised as data hub. Data available in a hub is highly curated and diverse business users can access this easily. It is a method of data integration where data is moved and re-indexed into a new system. It provides homogenised data in multiple desired formats. Instead of storing data in a single place, a data hub utilises multiple locations and formats. They provide agility in terms of getting data and value. A data hub is all about collecting and connecting data to provide meaningful insights which can become successful business decisions.
At Nu-Pie, the market intelligence wing is responsible for providing mission critical and industry specific market information, through analysis of internal data and external data to provide actionable insights to improve business growth. So, for the quick processing of vast amounts of market information, that is out there, we use a structured data base that allows for easy processing and quick critical insight generation. This has resulted in cliental.
Author: Jerrin Thomas; C0-Author: Benila Jacob