What Is Data Lake And Why Is It The Next Big Milestone In Data Management And Optimization

As per a research study done by Statista, it has been estimated that approximately 50 billion IoT devices will be in use by 2030.

And as today the pulse of digital life depends on wireless communications, hence to cater to this colossal requirement there would be an interminable increase in the number of consumer-grade and enterprise-grade network devices needed by the network to support more data and traffic than ever before.

This is because an increase in the number of connections would eventually result in an additional potential point of data.

Looking at this huge inflow of data generated through the network which will soon be in Petabytes to Zettabytes it would not be a wise decision to lose this data when it is true that in the present world we live in, banks on data to drive a plethora of business objectives.

In other words, data is the gold mine for most organizations because of the potential it represents for harnessing optimal business growth.

This increasing amount of data that we are talking about includes data from connected clients, transmissions and receiving traffic usage, browsing histories, traffic used by connected clients, alarms and notifications, reports, configuration data, client roaming histories, and many other details.

This magnitude, variety, and momentum of data from billions of devices are so enormous that networking companies are unable to gather and analyze the data to better understand business and customer requirements.

One reason for this incapability is the fact that legacy systems are no longer able to support the need and organizations are unable to gain a competitive edge by leveraging the inflow of massive data.

However, with the appropriate architecture and implementation of Data Lake, businesses can take complete advantage of critical insights and recommendations.

Data Lake, Analytics, and Beyond

Presently a varied amount of data from switches, access points, NAS (Network-Attached Storage), routers, and other network devices are collected and stored in different databases, data warehouses, and many other types of storage systems.

Hence now is the time when it calls for the need to centralize the data repository that allows storing, ingesting, discovering, analyzing, and visualizing all types of data.

A centralized data repository that is capable of containing structured (device logs, SSID, bytes transferred, CRM, POS, databases, etc.) data, semi-structured data, as well as nontabular raw unstructured data in its native form (like videos, social media feeds, enterprise systems, images, emails, blog contents, and more).

Data Lake is a technological wonder in modern times that is an ideal approach to harnessing the power of Big Data as it can be utilized to consolidate all network data in a single repository and can be saved “as it is”, without the requirement to impose a schema on the data upfront.

And businesses can benefit from Data Lake’s far-fetched powers by pulling out intelligent insights within seconds, without having to worry about infrastructural needs by implementing advanced analytics.

Key Benefits Of Using Data Lake

By implementing Data Lake, companies associated with networking can find numerous advantages as compared to legacy data warehouses.

A few of the key benefits of adopting Data Lake are:

  • Scalability: In terms of the diversity of the data sources handled, scalability ensures the accommodability of the growing amount of data in its raw and native form. More importantly without the immediate requirement of analyzing the data.
  • Analytics: Using Data Lake on-demand analytics can be done by simplifying Big Data and unlocking the full potential of this technology.
  • Data Availability: Availability and accessibility of data to several teams at any given instance enable the involvement of different hierarchies in the process of decision-making.
  • Data Authentication: Permits storage of data in different formats which helps in retaining data authenticity.
  • Flexibility: Transforming data in the present moment and using it later can be a really costly affair. With Data Lake establishments and individuals have the flexibility to transform data anytime in the future as and when they are needed.

Data Lake solutions can be implemented in an existing Network-Attached Storage solution as it enables companies to take advantage of the data for a wide variety of use cases that can be done without shifting or lifting the data when fresh data from network devices streams in.

Below are listed a few use cases that can aid companies to take advantage of critical insights and recommendations using Data Lake:

  • Network troubleshooting and optimization
  • Evaluating network performance
  • Network analysis based on location and time
  • Health monitoring of network devices
  • Micro targeted marketing
  • Segmentation based targeting
  • Social network feeds
  • Predictive analysis and many more

How SB Analytics Can Help Businesses?

SB Analytics is a Bangalore-based IT organization that is at par with its experience and expertise in implementing a scalable, secure, and governed Data Lake solution.

We work in tandem with businesses from defining the use cases, assessing and designing the architecture design, and thereafter implementing end-to-end Data Lake solutions right from data ingestion, data preparation, and data discovery to data visualization.

The solutions can be also customized as per specific business needs.

At SB Analytics, we bring together deep experience and expertise in several data management and analytics technology such as Hadoop, S3, Cassandra, Kafka, Redis, Elasticsearch, AWS Lake Formation, Apache Spark, Spark engine, Azure data bricks, Amazon Athena, and many more.

Being well versed with the latest technology and tools, the solutions can be deployed on AWS cloud, on-prem, or Azure cloud as per specific business needs.

Our Data Lake services enable our customers to take advantage of Data Lake solutions and provide the best-in-class user experiences.

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