What is a Data Lake?: Architecture, Benefits and More
Utilize the proficient strategy to modernize your business by incorporating a scalable and secure platform for a better data infrastructure from ingestion to storage to processing to analyses!
Quick Summary: The digital world is expanding with each passing day. And with the ever-rising use of technology, it is a given that a device is a home to substantial amounts of big data. The data is not always structured or polished. Here is a comprehensive guide on processing all the data and storing every micro byte of information in a single platform with easy accessibility!
2021 set a new bar for the amount of data created, copied, captured, and consumed (data volume) worldwide at approximately 79 zettabytes. Moreover, it does not show any sign of putting a brake on its growth. As per the estimates, the volume of data will cross the mark of 180 zettabytes by 2025.
In organizations, it is naturally common that the devices house disparate types of data, structured, semi-structured, and unstructured. Surprisingly, approx 90 percent of the data is semi-structured or unstructured. Many firms lack the strategies to convert external and internal data into resourceful information. They do not possess enough visibility of several business processes and customers’ behavior patterns. It makes it challenging to make timely and adequate decisions to minimize risk. You wouldn’t want to fall in that category, would you? Now, the question is how to store this data and process it quickly for use whenever it arises. Easy! Get data lake solutions for your company!
But what is a data lake? And how does it work? Keep on reading to find out!
What is a Data Lake?
A data lake refers to a central storage repository holding big data in a raw and granular format from several sources. The data can be structured, semi-structured, or unstructured. Data lakes store all the information in a more flexible form for future use.
Like one keeps things in a container, data lakes permit you to hold external and internal information, including IoT devices, on-premises applications, social media platforms, website clickstreams, etc. You can access and analyze this data using various tools, like machine-learning technology.
Data lakes are helpful for every industry vertical. You can use a data lake to enhance competence and incorporate predictive maintenance. It facilitates understanding the areas and causes of failure that need attention. You can adjust maintenance schedules to reduce repair costs and analyze production efficiency.
What is the architecture of a Data Lake?
Data lakes use a typical architecture process. Although there can be minor variations in details, the fundamental structure stays the same:
- Data Ingestion
As the name implies, this component connects data lake to external non-relational and relational sources like wearable devices or social media platforms and lots of polished, semi-polished, and unpolished data. The first step, ingestion, is done in real-time or in batches. However, you may need multiple technologies to ingest disparate kinds of data.
- Data Landing
All the data after ingestion is stored in the landing zone with unique identifiers and metadata tags. It is generally the largest zone in terms of volume used for analytic and operational purposes whenever the situation occurs. Data analysts and scientists experiment to define the scope and purpose of the available raw source data in data lakes.
- Data Processing
The data is moved forward to the processing stage once its purpose is known. Here refinement, aggregation, optimization, and quality standardization happen using various schemes. This step proves to be fruitful for several business use cases and reporting requirements.
- Refined Data Zone
After the processing, data scientists and analysts build specific data science and strategies to control the data processing. They repurpose the raw information into structures and high-quality to assist in further analysis or feature engineering.
- Consumption Zone
The last stage of data flow is the consumption or curated zone. Data scientists employ analytic consumption tools, SQL, and NoSQL query capabilities to avail the targeted audience, like a business analyst or a technical decision-maker, of the outcomes and insights from the analytic projects.
Why do organizations need a Data Lake?
Are you still debating whether your firm needs it or not? Here are a few reasons why you should incorporate a data lake to advance your business further:
- Increase in data generation
The staggering growth in data is simply astounding. Earlier in the 2000s, streaming was restricted to audio. Meanwhile, people used broadband only for web surfing, downloading, and emailing; the data usage was minimal. Now with over one-third of the population owning mobile phones and active engagements in social media, data has become a necessity. As the data is created consistently, is your repository ready to store all of it?
- Amount of unstructured data
Belonging to the corporate world in a digital era, you must have data from various sources, especially unpolished data. What is unstructured data? To put it simply, unstructured or unpolished data is an umbrella term for surveillance data, AI, media and entertainment data, invoices, emails, records, sensor data, etc. With various devices delivering information, it is high time you embrace an effective strategy to store and process all the unstructured data.
- Consumption of data
The global network, the internet, is unlike any other invention. The amount of data consumption worldwide on online platforms is simply eye-watering. Google executes more than 40,000 searches per second. Approximately 1.5 billion people are active on social media per day. Data is everywhere, and when calculated worldwide, its consumption is exponential. It is pivotal for companies to gather this kind of data to cover all aspects of operations, ranging from marketing to sales to communication.
- Deal with the changes big data brings
Primarily every company working through web or phone applications uses big data. Big data are voluminous and complex data sets, making it arduous for traditional software to process them. These data improve and enhance sales and marketing in a business. It further opens the door to loyal customers. However, to avail of it entirely, you must have a proper infrastructure to receive, retain, and retrieve information timely from the pile of data.
What are the benefits of a Data Lake to an organization?
You can use a data lake to keep the data secure for future reference. Because if you don’t stay on track in managing data effectively, the world will pass you by in every aspect of a business. Data lakes retain your data without any limitations or restrictions on volume, making it easy to access for training or threat-hunting purposes. Other benefits your organization can get with data lake solutions are:
- Greater agility
Nothing is constant, and business conditions are no exception. There are always new questions and chances approaching your firm that you know how to face. Data lakes offer greater flexibility than traditional tools while analyzing data. They aid you in adapting to the new market or economic changes quickly.
- Scalability at a reasonable price
Data lakes are comparatively cheaper and available at well-positioned rates than other tools. It is so because they run at low-cost hardware. You never know how and in what ways data can increase in the upcoming time. But, with data lakes, you’ll have a reliable data infrastructure.
- Instant implementation
You do not have to go through a prolonged schema-definition procedure to build a data lake for your organization. The platform requires no transformation of unpolished or semi-structured data. You can import the data in its raw form.
- More data sources
You can store any data in its raw form in a data lake. Experts and industry professionals can use these non-refined data to explore every aspect of the information and get in-depth insights over time.
How can NewEvol help your company?
It is better to accept that data is a part of life now. It enables unmatched discoveries and precise insight-driven decisions. Mixing it up with machine learning and artificial intelligence only boosts its significance in corporations. If you’re willing to do so, it all signals toward exceptional data lake solutions.
NewEvol is ceaseless when it comes to extending digital services. The data lake has become a must-have in corporations thanks to its practical analytics. Our data lake allows you to store tons of unpolished information without compromising its original form. You can gather and process petabytes of data instantly with our impressive solutions.
Our NewEvol offers exclusive features you can take advantage of:
- It provides a feasible way to analyze data without issues relating to its volume.
- The platform accompanies pre-packaged and effective data ingestion strategies to enable analysis from a central location.
- It stores the data and servers in a data center with on-premise security and assists in managing multi-domain services with its multi-tenancy.
Besides the features, our product promises to benefit you in multiple ways. For instance,
- NewEvol’s data lake comes with data visualizations using graphical elements to analyze massive amounts of information innovatively.
- It provides privacy and data compliance with a mix of standard security specifications.
- Its cluster-based structure makes it relatively easier to ingest more data by adding multiple nodes.
