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Data Management

Collect, store and use data securely, efficiently, and cost-effectively.Our goal is to help people, organizations, and businesses optimize the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximize the benefit to the organization .Let’s help you come up with a robust data management strategy, which is becoming more important than ever as organizations increasingly rely on intangible assets to create value.

  • What's included ?
    • Data Governance

      End-to-end support for your data governance program allows you to balance data demands while still adhering to regulations and internal controls. Ensure data is secure, private, accurate, available, and usable. It includes the actions people must take, the processes they must follow,

    • Data Architecture

      Let's help you set up principles that are made out of specific strategies, rules, models, and guidelines that manage, what kind of information is gathered, from where it is gathered, the course of action of gathered information, storing that information, using and getting the information into the systems.

    • Data Warehouse

      A system that is designed to enable and support your business intelligence (BI) activities, especially analytics. Data warehouses are solely intended to perform queries and analysis and often contain large amounts of historical data. The data within a data warehouse is usually derived from a wide range of sources such as application log files and transaction applications.

    • Data Intergration

      We'll help you unify data from different sources into a single, unified view. Integration begins with the ingestion process, and includes steps such as cleansing, ETL mapping, and transformation.Data integration ultimately enables analytics tools to produce effective, actionable business intelligence.

    • Data Preparation and Quality

      Process of cleaning and transforming raw data prior to processing and analysis. It is an important step prior to processing and often involves reformatting data, making corrections to data, and combining datasets to enrich data.

                                                                                                                                                                 



See, understand, and act on data

Simplified Data Analytics

Our modern distributed data architecture that includes shared data assets and optimized data fabric pipelines that you can use to address today's data challenges in a unified way that'll help your business respond faster to urgent data requirements with less data engineering effort and lower infrastructure costs.We can begin the below process together to reduce the time between data capture and informed decisions and actions, and become a real-time, data-driven business.

  • Here's how we'll get started.
    1

    Business Understanding.

    What types of insights do you want to derive from data analysis? While you can get many varying insights from raw data, data analysis should be aimed at solving specific, pre-identified problems.We'll work with other departments within the organization to define problem statements and acquire an intimate knowledge of the business and its present needs and future goals. It also requires data about the business’s key performance indicators (KPIs) and other important metrics.
    2

    Collect, Extract and Transform data.

    Businesses generate tons of data containing different types of insights from the different sources which is stored in a data lake which is then extracted to create a final data set that leads the further analyzing process to create a clean data set.The data is then transformed into particular structured data in such manner that it can be used at a destination for analysis process this process is known as ETL(Extract Transform Load)
    3

    Analyzing the cleaned data.

    Depending on the data type and the objective we could come up with a descriptive analysis to yields insights that have already happened and give a clearer view of the problem statement,diagnostic analysis to explains why something has happened and are crucial to solving the problem and reaching the objectives, Predictive analysis derives insights about what is most likely to happen in the future based on historical data, Prescriptive analysis offers recommendations about what to do in the future based on the other analyses’ insights. Ideally, it should offer solutions on how to achieve your set objectives.
    4

    Interpreting and Data Visualization.

    After building or creating the datasets, we need to visualize data to develop your Hypothesis or Insights to explore and evaluate the data.

We'd love to be part of your success story

About Sahili

Founded in 2022, Sahili began as a data analytics company working on automation, big data and customer understanding technologies all oriented at utilizing customer insights for better customer engagement and has continued to build on that foundation to grow, evolve and keep up with rapid changes in trying to simplify IT Solutions.



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