Case study Telecoms company cuts data management costs over 20x by offloading its data from Data Warehouse to a Data Lake. Download full case study here.
What is Data Lake?
In a time of intensive digital transformation, many companies are being overwhelmed by massive amounts of data. And traditional data warehouses are simply not able to acquire, store, integrate and process it all.
One solution is Enterprise Data Warehouses (EDWs), but they are designed with a clear focus only on structured data and strict data models. So, while EDWs can continue to offer some support to your business, another data management platform has emerged that can overcome new challenges and accelerate your digital shift – a data lake.
Data lake is a hub which centralizes all enterprise data captured from multiple sources into one logical platform. It provides a foundation for managing big quantities of data in a consistent way with new, real-time capabilities and use cases. Crucially, data lake platforms can tackle both structured and unstructured data.
As a result, data lake enables your business to identify trends and get immediate insights from big data analytics, machine learning and data discovery, and all much faster than before.
10 Reasons your Enterprise
needs to incorporate a Data Lake
Data lake platforms can give your business a real competitive edge. Here are 10 great things you’ll be able to do once you have a data lake incorporated into your enterprise:
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1. Develop a data-driven company culture
A data lake will enable you to build a strong data foundation for a unified digital enterprise, facilitate a data-driven mindset within your team, and make it easier to extract actionable insights from your data. This will help you avoid being disrupted and displaced by competitors that are more agile.
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2. Turn your data into a valuable asset
Build a solid ground for advanced analytics and customer-focused decision making by collecting data centrally, whatever the volume and variety of the data you are dealing. At present, 60-73% of all data within an enterprise goes unused for analytics1, but with a data lake you can leverage all this data and improve performance.
-
3. Exploit the potential of your data faster
Using data lake architecture, you will be able to process data faster and use real-time functionalities to create data-driven, targeted business insights, all in a much shorter time than with other data management platforms.
-
4. Employ Artificial Intelligence (AI) driven tools
Your data lake can be the foundation for experimenting with advanced analytical techniques and rapidly developing AI driven analytical models, which will enable you to build on your existing competitive advantage or catch up with the competition quickly.
Source: 1. Forrester Wave: Big Data Hadoop Distributions, 2016
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5. Depend less on limited internal resources
Data lake allows different organizational functions to work in their own sandboxes, and all with user-friendly data management tools. Your employees will be able to leverage big data easily and efficiently, without being heavily dependent on IT & BI departments.
-
6. Enable day-to-day knowledge sharing
You will be able to share information and know-how effectively both internally and externally across the business value chain by using a data lake for your enterprise data management.
-
7. Guarantee information quality
A data lake can provide data that’s easy to find, accessible and usable, and best of all you know that all of this data is of the very highest quality.
-
8. Gain meaningful cost-efficiency
Significant economy effect can be achieved by adopting a low-cost architecture, all organized around an open-source data management platform.
-
9. Integrate insights from different business systems
Efficiently consolidate business intelligence and analytics from all the systems functioning in your organization: payment, supply chain & logistics, procurement, marketing & sales, HR, and more.
-
10. Ensure comprehensive compliance
With data lake, you will be able to ensure security of your data and comply to the latest data privacy regulations effective in your markets, for example, the EU’s new General Data Protection Regulation (GDPR).
-
1. Develop a data-driven company culture
A data lake will enable you to build a strong data foundation for a unified digital enterprise, facilitate a data-driven mindset within your team, and make it easier to extract actionable insights from your data. This will help you avoid being disrupted and displaced by competitors that are more agile.
-
2. Turn your data into a valuable asset
Build a solid ground for advanced analytics and customer-focused decision making by collecting data centrally, whatever the volume and variety of the data you are dealing. At present, 60-73% of all data within an enterprise goes unused for analytics1, but with a data lake you can leverage all this data and improve performance.
-
3. Exploit the potential of your data faster
Using data lake architecture, you will be able to process data faster and use real-time functionalities to create data-driven, targeted business insights, all in a much shorter time than with other data management platforms.
-
4. Employ Artificial Intelligence (AI) driven tools
Your data lake can be the foundation for experimenting with advanced analytical techniques and rapidly developing AI driven analytical models, which will enable you to build on your existing competitive advantage or catch up with the competition quickly.
Source: 1. Forrester Wave: Big Data Hadoop Distributions, 2016
-
5. Depend less on limited internal resources
Data lake allows different organizational functions to work in their own sandboxes, and all with user-friendly data management tools. Your employees will be able to leverage big data easily and efficiently, without being heavily dependent on IT & BI departments.
-
6. Enable day-to-day knowledge sharing
You will be able to share information and know-how effectively both internally and externally across the business value chain by using a data lake for your enterprise data management.
-
7. Guarantee information quality
A data lake can provide data that’s easy to find, accessible and usable, and best of all you know that all of this data is of the very highest quality.
-
8. Gain meaningful cost-efficiency
Significant economy effect can be achieved by adopting a low-cost architecture, all organized around an open-source data management platform.
-
9. Integrate insights from different business systems
Efficiently consolidate business intelligence and analytics from all the systems functioning in your organization: payment, supply chain & logistics, procurement, marketing & sales, HR, and more.
-
10. Ensure comprehensive compliance
With data lake, you will be able to ensure security of your data and comply to the latest data privacy regulations effective in your markets, for example, the EU’s new General Data Protection Regulation (GDPR).
Traditional DW platform |
Data Lake on Hadoop |
|
|---|---|---|
| Handles structured and unstructured data of any form | ~ | ✓ |
| Is highly scalable and efficiently runs huge data workloads | ~ | ✓ |
| Data processing speed rises linearly with hardware capacity | ~ | ✓ |
| Petabyte-scale data storage capacity | ✖ | ✓ |
| Runs open source software | ✖ | ✓ |
| Suitable for use with affordable commodity hardware | ✖ | ✓ |
| Enables the efficient execution of AI and machine learning workloads | ✖ | ✓ |
✓ – yes, x – no, ~ – partially
The Main Challenges
of Bringing a Data Lake on Board
Deploying a data lake requires expertise in big data management and a huge amount of input from our company’s IT specialists. We don’t have this expertise in-house, so how can we move forward?
Complex coding may be needed for the implementation of data loading and data cleaning. How do we get to the analysis stage faster?
Data lake could be a ticking time bomb for privacy and data security issues if insufficient consideration is paid to these requirements at the design stage. How do we get the expertise to make sure we’re doing things correctly?
Without proper data governance, a data lake can end up being a “data swamp” that is not analytics-friendly and doesn’t bring the value to the business that we expected. How can we avoid this outcome?
Important points
about enterprise data management to consider
1. Automating as many
actions as possible
2. Integrating different
source systems smoothly
3. Ensuring a short data
platform set-up time
4. Complying with data
privacy requirements
Exacaster Data Lake Solution:
Painless Adoption of Big Data
Central data hub at a low cost
We design data lakes to be fully integrated into your existing IT infrastructure. This means our data lake solution becomes a single data management platform for your entire enterprise.
Once we have built and set up a data lake for you, there will be no need to change the architecture of your data infrastructure for many years to come. And that’s true regardless of the way your business develops and whatever new IT elements or services arrive in the future.
With Exacaster Data Lake, you can be sure that you have made a sound investment into your data foundation, leaving you to focus on leveraging data for better business insights rather than spending your time and money on endless platform fine-tuning.
Fully managed service
Exacaster specializes in delivering data lakes as a fully managed service. We use our nearly 10 years’ of expertise in building and managing big data platforms to maximize the value generated by the data lake solution while minimizing the amount of input needed from your organization. We can provide short time-to-market while comprehensively addressing the main challenges of enterprise data management.
Exacaster Data Lake comes with a low-effort data import guarantee. We take care of identifying and loading all the data for you within our agreed SLA. All the automation tools we use are pre-tested, and we also employ proven data import and quality assurance methods. As a result, you won’t need to procure any additional software or hire costly Hadoop specialists, either to train your IT staff to administer your big data platform. We take care of all this.
Compliance and security
Exacaster Data Lake comes with a EU’s General Data Protection Regulation (GDPR) compliance best practice blueprint. A strong initial data governance review is carried out during the first phase of implementation. During this process all data is thoroughly classified and labeled. And with our solution, a policy-driven process of governance and data anonymization is rolled out, ensuring both the compliance and security of your data.
Advanced analytical capabilities
Exacaster’s Data Lake solution enables you to leverage big data in the ways that best meet your business needs. A diverse range of commercial and open-source data science tools driven by artificial intelligence (AI) can be operated on the Exacaster Data Lake, empowering your data-driven business with smart insights.
Exacaster’s fully managed Data Lake service vs the alternatives
There are at least seven major elements you need to consider carefully when implementing your big data platform. And the Exacaster Data Lake solution covers all of them in a one-stop shop offering.
| 7 elements of big data management platform |
Exacaster Data Lake solution (on-premises or cloud) |
Do it yourself strategy |
|---|---|---|
 Big data architecture design & integration plan |
 |
Your own responsibility |
 Hardware |
 |
Your own responsibility |
 Software |
 |
Your own responsibility |
 Solution installation |
|
Your own responsibility |
 Data loading (ETL) configuration |
|
Your own responsibility |
 24/7 service operation, including data import supervision |
|
Your own responsibility |
 Data privacy regulation compliance (GDPR) |
|
Your own responsibility |
| 7 elements of big data management platform |
Exacaster Data Lake solution (on-premises or cloud) |
Do it yourself strategy |
|---|---|---|
| Big data architecture design & integration plan | |
Your own responsibility |
| Hardware | |
Your own responsibility |
| Software | |
Your own responsibility |
| Solution installation | |
Your own responsibility |
| Data loading (ETL) configuration | |
Your own responsibility |
| 24/7 service operation, including data import supervision | |
Your own responsibility |
| Data privacy regulation compliance (GDPR) | |
Your own responsibility |
1. We procure hardware on your behalf from our cloud partners or provide sizing recommendations if you want to have your own.
2. We use proven software of our cloud partners and independent software vendors to operate a tailored and fully integrated data lake platform for you.
Exacaster Data Lake Solution
in a Nutshell
While every data lake solution is tailored, the stages of implementation follow a similar pattern.
We start with the Assessment & Design stage, then proceed to the Transform stage and end with the Operation stage.
Who Can Benefit from a Fully Managed Data Lake?
Mid-sized organizations
Mid-sized organizations can derive significant value from their data with Exacaster’s fully managed Data Lake service. No previous experience or knowledge of big data platform management is necessary.
Global enterprises
Global enterprises can enhance their expertise in managing big data by replacing or supplementing their existing big data platforms. And the Exacaster data lake accelerates time-to-market so your analytical solutions are up and running sooner.
Global enterprises
Global enterprises can enhance their expertise in managing big data by replacing or supplementing their existing big data platforms. And the Exacaster data lake accelerates time-to-market so your analytical solutions are up and running sooner.
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