02nd Dec, 2020
, , Designation
While the word about data lakes has been out since last couple of years, industry understanding and adoption needle has now finally started to move from ‘just talks’ to ‘action’. The reason for this is simple – to bring simplicity, intelligence and efficiency into data management.
As it is, the volume, variety, velocity and veracity of big data are getting increasingly complex each passing day. The way the data is stored, processed, managed and shared with decision-makers is getting impacted by this complexity and to tackle the same, an intelligent approach was becoming a dire need.
What is Data Lake?
To avoid any confusion with similar nomenclatures in the realm of big data, let’s begin from ground zero.
As the name suggests, data lake is a large reservoir of data – structured or unstructured, fed through disparate channels. The data is fed through channels in an ad-hoc manner into these data lakes, however, owing to the predefined set of rules or schema, the correlation between the database is established automatically to help with the extraction of meaningful information.
It provides a high level of flexibility in terms of interaction with and leverage of the data. In general, data lakes are used to store data when you’ve a constant stream of unstructured data coming into, such as web interactions, product logs, IoT sensors, app usage etc.
Data Lakes & Sales Ecosystem – Connecting the Dots
With sales moving beyond product features and becoming more storytelling and personalisation oriented, a deeper understanding and connection with the customer is the need of the hour.
Having the wealth of customer database at disposal, it all boils down to having an intelligent and actionable analysis out of it and that’s where data lakes come into the picture.
Following elucidates some of the challenges of the sales ecosystem which are solved by Data lakes:
Need for Data in Native Format
Since the amount of data being generated by enterprises is extremely huge, a major portion of that data is discarded. A remaining small portion is then stored in the data warehouse – for a few years. This happens to owe to the storage capacity limitations, structure restriction, associated costs etc. and most of the time it happens because enterprises don’t know what to be done with that data, esp. machine-generated or historical data. Hence, it is dumped away, thus putting a limitation on the extent of analytics application that can happen.
With data lakes, enterprises save the data without fretting about the structure, intended use etc. Hence, whenever you may need that data, you’d be getting it in its native format.
Quashing Data Silos
With multiple teams and departments, it’s a general scenario that database is not centralised and instead remain in silos because it turns out to be expensive as well as time-consuming to share that data with one another.
It is like having an immense wealth with you but not being able to use it owing to the labours it is going to take to spend it.
This issue is tackled head-on with data lakes because there the data ingestion is almost frictionless since it accepts data without any processing, thus allows for deeper data leverage to all with a centralised and transparent access process. Data ownership doesn’t remain a barrier any more with data lakes.
Advantages of Using a Data Lake
The acceptance of the need for data lakes itself makes visible a lot of benefits which salespeople can accrue, let’s dig deeper and see what all as an organisation are you set to gain if your database strategies include leveraging data lakes:
Say good-bye to silos and fragmentation
With data lakes, you get a unified view of everything which comprises the customer experience – all the data from all the platforms, departments, teams, delivery channels.
Better preparedness for the customer journey
Since you’ve better knowledge about the customer buying cycle, the high or low points of his journey, quite naturally the decision-making process is much more impactful than before.
High yielding campaigns
You’re better equipped than before for generating and assessing campaigns. The agility and autonomy are rendered by the tools which not only helps you to measure but also to optimise your marketing investments in real time.
Power to predict
Sitting on the historical data which you’d have otherwise dumped or would have never been able to analyse, provides you with the power to analyse and establish predictive models for customer behaviour.
All touch point control
You’re also able to trace the journey and behaviour specific to each customer touchpoint which allows you to rank the point of conversions accurately. Accordingly, you can adjust your focus on the touchpoints.
A fertile environment for new tools or methodologies development
Since you own the storage of immense amount of data, you can generate your own technological environment and a service-oriented architecture which can make the development of new tools possible.
Intelligent and faster decisions
With dynamic dashboards which work upon varied kinds of data accumulated from myriad number of sources – external or internal, you get an unmatched business intelligence right at your tips and thus, decision-making in real-time becomes possible.
If we put together all these benefits in one basket, the highlight of data lake adoption would be the provision of an agile 360-degree view data-driven marketing operations and a faster (and intelligent) response system to any business need.
These will automatically translate into improved customer interactions, enhanced R&D innovation possibilities and augmented operational efficiencies.
Convinced about the adoption of data lakes?