Combining the power of a data warehouse and data lake for business successBlog by Glorious Insight
Combining the power of a data warehouse and data lake for business success
Data has become the most valued asset for the companies and has also grown complex. Its enormity and diversity in terms of type, structure, source, and format have made it extremely difficult for businesses to capture, filter, and use their data. With increasing complexity, businesses are facing many more challenges in data management than they have ever before. The introduction of cloud computing has completely transformed the way data is perceived and consumed.
In the present day and age, large volumes of data are being generated every second. Presenting an intricate challenge of storing it efficiently that facilitates easy and quick access and management. Most companies, regardless of their respective industries, prefer data warehouses and data lakes for efficient storage.
Today, data warehouses and data lakes are the central components of database architecture. These repositories serve the purpose of agility, flexibility, and scalability for modern businesses. It is also possible to democratize data to meet the requirement of any number of users by defining roles and purposes of accessing it.
Glorious Insight has worked with several leading companies in various industries and reinvented their data culture. We provide database management solutions including data warehouse and data lake and help the companies to align in a position to accommodate this significant shift. Data management and analytics are critical to business operations and outcomes. Our experts hold extensive experience and domain knowledge and customize the data architecture to meet your requirements.
Combining a data lake with your conventional data warehouse is the first step to smart data management and takes the flexibility and speed of data processing and collection up by a notch. It is also efficient in terms of cost.
Reports suggest that earlier the majority of the companies, nearly 52%, choose Hadoop to deploy data lakes for cost-effectiveness. However, according to Gartner's prediction, more companies will choose standard RDBMS for the purpose and 30% of companies will achieve the target at the lesser or same cost.
It simplifies and organizes the collection of stream data and data in semistructured and unstructured forms. The combination also vacates the data warehouse bandwidth that can be utilized for business analytics. It is one of those rare expenses that produce guaranteed ROI.
Exploring data lakes and data warehouses
Data keeps entering the system for all businesses, especially in the present digital market spaces. Most of the data is unorganized and unstructured. It is often not possible to create data models before storing the data at such a high pace. This is where data lakes are the best solutions. These repositories can store piles of data entering rapidly into the system in its natural raw format.
Companies generally have a huge single data lake that stores raw data from various sources and transformed data that can be used for reporting, advanced analytics, machine learning, and visualization. Experts assert that within two years of its introduction nearly 20% of companies had a data lake and more than 40% planned to deploy within a year.
A data lake can be understood as a single water body that has a variety of data streams bringing data in and allowing managers to take data for examination. It is particularly useful to hold diverse data from differing sources. It includes structured relational databases, semi-structured files data from logs, XML, etc, unstructured emails and documents, and binary images, audios, and videos. It is a cost-effective method to store this large mixed bag of data.
On the contrary, a data warehouse stores all the data in an organized structured form, regardless of its original structure. This is where the actual value of data is derived. It provides real insight into the data and facilitates enhanced, real-time, and fact-based decision-making. After filtering, segmenting, and organizing, data is fed into the warehouse that serves as the key to analytics dashboards, advanced analytics, report generation, etc.
As all the necessary data is stored at a central warehouse, organizations can make quick and informed decisions rather than slow and intuition-based calls. Significant improvement in business intelligence boosted the outcomes of key initiatives leading to greater optimization and high profitability.
Glorious Insight creates customized solutions using the best of the ability of both, warehouses and lakes. Utilizing the capabilities of both kinds of repositories, we deliver systems that accelerate analytics and enable real-time decision-making.
Strengthening of warehouses and lakes
Having a detailed understanding of individual storage technologies, let us look into the combined power of the two. A data lake is a place where raw data is stored from a wide range of sources. Data scientists and business users work on this data to clean, manipulate, transform, and organize it.
A managed data lake uses database management platforms to organize the instream data, apply metadata, and enforce data governance over it. It gives a clear picture of the data stored in the lake so that it can be used with confidence.
Now you already have the data and know, how it looks and what it is exactly about. The next step is to enhance the data to draw valuable insight from it. The data warehouse holds organized data and is directly linked to business intelligence tools. Augmenting the data lake with these two components adds to the strength of the warehouse.
A complementary data lake is created and added to the warehouse and analytics tools. This speeds up the extraction of important data and creates reports, predictive models, and BI visualizations in real-time.
The need for enhancement
Often companies question the combination and augmentation of data warehouses and data lakes. Having worked with several leaders and promising companies from a wide range of industries, Glorious Insights' team could find the two basic reasons to go for augmentation. These two compelling reasons are blue sky and cost-cutting. These factors encourage most of the companies to extend the capabilities of their data repositories and draw definite benefits from their investments.
Today, companies cannot survive without innovation and out-of-the-box-solutions. Sometimes the quest of providing new and unique services and products forces the companies to go over and above the capacity of their processes.
When innovations require data management that requires capabilities that are out of the range of a data warehouse, augmentation is needed to find new insights through advanced big data analytics.
When you want to reduce the cost of operations while continuing with your present warehouse by leveraging commodity hardware, augmentation is needed.
In both the above cases, combining a data lake can result in remarkable improvement in flexibility and acceleration. As data navigate faster through the data lake, the combination mitigates the latency and reduces the time-to-insight. Data lakes also support streaming data that ensures uninterrupted flow of real-time data in contrast to the batch-updates in warehouses.
The big data step to future
Enhancement and optimization of modern data warehouses is just the first step, data lakes allow companies to do much more with their data. Glorious Insight develops specialized solutions for extracting the maximum value of your enterprise data. We utilize the best tools and create unparalleled database architecture that transforms the way you perceive your data and enables rapid business growth and fulfillment of business objectives.
The amalgamation of data lake and data warehouse is considered a huge step into the future of big data and big data analytics. The addition of data lake brings in flexibility, scalability, and agility in analytics processes for the rapid discovery of insights.