Nogamy Think
expert consulting -
The smart way to reach decisions
You should plan your Data Analytics
carefully, using know-how
and best practices
from experienced professionals
Defining a Data analytics strategy, designing the adequate architecture and matching the correct technology to your organization’s needs – This is exactly what our experts can help you with.
The expertise of our professionals covers a broad range, from the data infrastructure, the integration, and data model layer to the visualization, reporting and analysis layers.
We are committed to top-notch service in assisting you to plan the best Data Analytics solution for your needs.
1. Data Analytics roadmap
whether you are considering an establishment of a BI / BigData / Advanced Analytics solution, or you already have one and are considering how to take it to the next level - we will provide you with a plan for moving forward.
Our roadmap methodology will process your data requirements (current and expected), analyze your data sources, and will create a recommendation for an advanced data analytics solution.
The recommendation will include four elements:
1 - Prioritized list of clear business requirements.
2 - Logical data model for a DWH \ Semantic layer.
3 - Architecture and tools for end2end data pipeline.
4 - Work plan, phased and practical for developing the Data Analytics solution
1. Data Analytics roadmap
whether you are considering an establishment of a BI / BigData / Advanced Analytics solution, or you already have one and are considering how to take it to the next level - we will provide you with a plan for moving forward. Our roadmap methodology will process your data requirements (current and expected), analyze your data sources, and will create a recommendation for an advanced data analytics solution. The recommendation will include four elements: 1 - Prioritized list of clear business requirements. 2 - Logical data model for a DWH \ Semantic layer. 3 - Architecture and tools for end2end data pipeline. 4 - Work plan, phased and practical for developing the Data Analytics solution
2. Establishing your Data Analytics array on the cloud
Do you have an existing on-premises BI \ Data Analytics array and you wish to convert it to the cloud?
We will help you plan it, choosing the right cloud environment and tools.
the conversion plan will be constructed to minimize the risks of service loss, performance problems, security issues and data inaccuracy.
After careful planning we can do the actual conversion and implementation for you.
2. Establishing your Data Analytics array on the cloud
Do you have an existing on-premises BI \ Data Analytics array and you wish to convert it to the cloud? We will help you plan it, choosing the right cloud environment and tools. the conversion plan will be constructed to minimize the risks of service loss, performance problems, security issues and data inaccuracy. After careful planning we can do the actual conversion and implementation for you.
3. BigData architecture plan
Whether you already have a Data Analytics array or not, you might be considering the establishment of an array that supports big data.
Such an array can be an evolution of your current Data Analytics assets without having to throw away all your previous investment in it.
In any case, the architecture and tool options are vast in the BigData arena, so we offer a process which examines your needs and your data sources to plan the optimal fit for you.
3. BigData architecture plan
Whether you already have a Data Analytics array or not, you might be considering the establishment of an array that supports big data. Such an array can be an evolution of your current Data Analytics assets without having to throw away all your previous investment in it. In any case, the architecture and tool options are vast in the BigData arena, so we offer a process which examines your needs and your data sources to plan the optimal fit for you.
4. Data Science use cases implementation
If you have reached a decision that it is time to take your analytics to the next level and extract more business value from it, maybe using Data Science models is for you.
First, a plan for a successful initiative must be devised. The plan should include several crucial ingredients:
A) A list of use cases. Such that can potentially bring substantial business value and cannot be solved using standard tools of analysis.
B) A methodology and set of tools for the Data Scientist.
C) Competent professionals for doing the job.
D) Data sources that will serve as input to the use cases and a plan as to how to extract the relevant and cleansed portion of it.
4. Data Science use cases implementation
If you have reached a decision that it is time to take your analytics to the next level and extract more business value from it, maybe using Data Science models is for you. First, a plan for a successful initiative must be devised. The plan should include several crucial ingredients: A) A list of use cases. Such that can potentially bring substantial business value and cannot be solved using standard tools of analysis. B) A methodology and set of tools for the Data Scientist. C) Competent professionals for doing the job. D) Data sources that will serve as input to the use cases and a plan as to how to extract the relevant and cleansed portion of it.
5. Selecting the right BI \ BigData software & hardware
In some cases, a full Roadmap plan is not the requirement but rather only the technological tools and architecture decision's part.
This is relevant when you already have the goals of Data Analytics set up and you have a detail design of the KPIs, reports, analysis that you require.
Tool selection must be made for all layers of the data array - ELT\ETL , Storage of data model (ODS, DWH, Data Lake), BI application, Data Science tools.
The comparison of tools should consider both on-premises and cloud options.
5. Selecting the right BI \ BigData software & hardware
In some cases, a full Roadmap plan is not the requirement but rather only the technological tools and architecture decision's part. This is relevant when you already have the goals of Data Analytics set up and you have a detail design of the KPIs, reports, analysis that you require. Tool selection must be made for all layers of the data array - ELT\ETL , Storage of data model (ODS, DWH, Data Lake), BI application, Data Science tools. The comparison of tools should consider both on-premises and cloud options.
What is the business engagement model for this service?
We will fit the business engagement terms to your preference. It can be based on hourly tariffs, monthly tariff or priced per a scoped task.
There is a BI application that we are considering, how can you assist us?
Nogamy has a methodology for comparing different sets of tools based on different criteria in the Data Analytics domain. Coupled with hands-on experience with many of the tools, we can analyze your needs and recommend the best ones for you..
How objective is Nogamy in its recommendations?
Nogamy's core business is implementing customized data analytics solutions that best fits an organization needs. We are committed to unbiased recommendations which will be based only on what's best for you.
Can you also implement the roadmaps and recommendations that you prescribe?
Absolutely! "We put our money where our mouth is.."