With ever increasing amount of data, type of data and datasources (log, social media, API, IOT, RDBMS, NoSQL etc), more and more organizations are looking to implement data lakes rather than Data Warehouse.
DAXOR IT has got very well qualified resources as well as plenty of experience (including various domains and geographies) in implementing end to end data lake solutions. Being a new technology, we can also help you understanding the cost and benefit analysis early on but also help in understanding it.
Data Lake allows you to store data not just from your historical transactional data sources, but also multiple other sources and it can be of different variety of data as-is. Data lake architecture helps you to keep the data as coming from the source, without first fitting to your needs which is unlike data warehouse architecture. That is the differentiating factor which makes not only changes to data but also to the analytics that runs around them.
Data lake can hold information for you from log files, DBs, every click that customer generates, social media pages, or any diverse source that you need to incorporate. Therefore, architecture becomes crucial to ensure data integrity, our data lake experts shall provide you with the data lake solution that fits your current and future needs. Our data lake consultant shall ensure to give you the entire picture of end-to-end solution for your needs. If there are additional services that are required like cloud data lake and data warehouse services, or specific data lake analytics needs to be built out for making the best use of the information to you, our enterprise data lake services.
1) Identifying the data needs
2) Connection to the data sources
3) Transforming the structure and unstructured data on which analysis could be done
4) Implementation and deployment of the solution on-prem or cloud
5) Reporting, dashboarding and visualization
6) Prediction and forecasting
Roadmap and strategy to build architecture and solution
Technology stack selection : On cloud or in prem solutions
👉 Create a data lake reservoir for data from within enterprise, or social media sources, and other device information. To start off with providing a small prototype first
👉 Provide you with a scalable data storage which can handle Petabytes of data for your data computing, and access data layers
👉 We will help you to enable data governance and enterprise-wide access controls for data security and integrity.
👉 We will help you to reduce the time to access and locate data and accelerate data preparation and reuse the information.
👉 We help you with building and testing customized analytics models around the new data lake solution.
👉 We also help you to trace the data lineage and ensure quality of data is uncompromised to deliver reliable insights.
👉 Helping in training internal resources, deployment and maintenance as well as seamless adoption across organization
👉 Based on your needs our experts will also suggest if any related additional services are required like
👉 Business Intelligence solutions or services for effective data lake analytics for dashboards and reporting visualization
👉 Data warehouse integration or upgrades to be in sync with data lake solutions and migration of data for permanent storage to data marts.
👉 Artificial Intelligence or cognitive computing or machine learning algorithms to digest the new data coming into data lake every day.
👉 Data science solutions to custom statistical models and algorithms for real time data analytics.
While you are looking for building the data lake, we can work with you closely and based on your technology preference, budget, data security outlook and other technology stack we can also provide you consulting on the technology stack which should be used.
We can work on
Hadoop : With this we can help in implementing data lake on-prem or your own servers
AWS : S3 technology of Amazon web services can be used for implementing data lake. AWS being the most mature and feature rich cloud provider, there are many other associated services which could be used like Redshift, EC2, Glue, Quicksight, Sagemake, MapReduce etc.
GCP (by Google): Google Cloud storage (GCS) of GCP stack can also be used for designing and implementing data lake. There are other set of tools also offered by Google which can be used in conjuction including Google Data Studio / Looker, Google Big Query to name a few.
Azure (by Microsoft) : Azure Data Lake Store (ADLS) can also be an excellent choice for implementing the Data lakes. Like AWS, Azure also many other services for data integration, PowerBI etc.
Snowflake Cloud Data Platform : Snowflake technology can also be used to create data lakes. Snowflake is the world’s leading cloud DW provider. Snowflake can also work on any of the above mentioned cloud platform’s as well.