Data Intelligence Services

DATA INTELLIGENCE SERVICES

Transforming Data into actionable insights

We help companies use data to improve their business by making informed decisions faster, based on conclusive insights

data intelligence services

How Big Data Solutions helps businesses

Cost reduction

Using big data allows businesses to identify and fix inefficiencies, streamline proc esses, and incorporate feedback—enabling organizations to avoid any wastage, work faster, and increase profits in short or long time.

Improved products and services

Big data analysis helps in identifying customer needs, ascertain satisfaction, and make changes as insights are uncovered. For established brands, data analytics allow them to avoid the guesswork linked with product development and make it easy to give customers exactly what they like.

Better decision-making

Big data facilitates smarter decision-making—fast. Businesses can now analyze loads of information in real-time and make crucial strategic decisions based on unerring data.

Industries That Benefit the Most from Data Intelligence

Advertising
E-commerce
Medicine
Banking and Finance
Construction
Transport & Logistics
Education
Manufacturing
Energy and Utilities
Government

Our Data Intelligence Offerings

Data Strategy

At Growexx, we focus on transforming businesses to be more data-centric and to deliver improved value by utilizing meaningful data. Our technology and domain experts work your team to understand organization’s vision. Collaborating with the business teams, we help them define a customized data strategy roadmap, which includes laying out a step-by-step process after analyzing key data sources, transformation, storage, and access – likewise, we help enterprises achieve their goals by being data-driven. This roadmap encompasses activities that include identifying tools and laying out processes for specific data management, cloud-based data transformation, visual, storage, and advanced analytics data solutions.

Data Management and Business Intelligence

We think big and act fast. Our team ensures that the product is released quickly while keeping the scope of scaling as top priority after the launch.Our team at Growexx focusses on delivering customized and scalable services in congruence with our clients’ business goals enabling them to achieve improved efficiency and accelerated growth. We help organizations achieve data excellence by setting up the right infrastructure for data storage and putting in place the right people and data processes that enable effective data management. We also help organizations in evaluating various data management concepts, technologies, and processes. We assist organizations in choosing the best technology according to their customized needs, be it on-premises, in the cloud, or multi-cloud solutions. Our highly skilled team of talented data engineers provides best-in-class data management services with utmost adherence to data security norms and practices.

Visual Analytics/Data Visualization

Equipped with the latest algorithms and tools, our team at Growexx allows enterprises to access and capitalize on the vast potential of data by providing customized visual analytics solutions. Flexible, animated, and immersive visual analytics is a capability that allows business leaders to think out of the box. It makes it possible to identify trends, patterns, and outliers and draw substantial insights to enable better decision making. Our data visualization experts understand and differentiate between various tools available enabling them to pick the best tool suited for the client’s needs.

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Our Data
Analytics
process

01

Defining the questions

It is a general practice that in organizational or business data analysis, one must begin with asking measurable, clear and concise questions. For example, we start with a clearly defined problem: A team is experiencing rising costs and is no longer able to submit competitive contract proposals. One of the questions to solve this business problem might include: Can the company reduce its staff without compromising quality?

02

Data collection

Once we established a clear objective, we start creating a strategy for collecting and aggregating the appropriate data. A key part of this is determining which data is needed. This might be qualitative (descriptive) data, such as customer reviews, or quantitative (numeric) data, e.g. sales figures. All data fit into one of these three categories: first-party, second-party, and third-party data. At this stage, we make it clear which Data management platform we’re using in this case.
03

Data cleaning

Once the data is collected, the next step is to get it ready for analysis. A good analyst spends maximum time in a project cleaning the data. This process includes the below tasks-

  • Removing unwanted data points
  • Removing errors, outliers
  • Structuring the data
  • Filling data gaps

Our team uses many open-sources data tools for these purposes. However, for very large database or ‘heavy scrubbing’, we use Python libraries (e.g. Pandas) and some R packages.

04

Data Analysis

Now comes the real deal- analyzing the data. The type of data analysis we carry out largely depends on the customized goals of different clients. However, we deploy many techniques; Univariate or bivariate analysis, time-series, and regression analysis are just a few to name. Broadly speaking, all data analysis can be described by the following categories-

  • Diagnostic analysis to focus on why something has happened
  • Descriptive analysis to identify what has already happened
  • Predictive analysis allows us to identify future trends based on the above two analysis
  • Prescriptive analysis allows us to make recommendations for the future
05

Presenting the results

Now, as we complete data analysis, we have the insights which needs to be presented to the clients in the most logical, self-explanatory way. We deploy a few data visualization tools such as Google Charts, Tableau, Datawrapper, etc. Apart from these, our team’s familiarity with Python allows us access to many data visualization libraries and packages available. Our team has worked with multiple clients over these many years and have gained immense experience in presenting complex data in the easiest way by using reports, dashboards, and interactive visualizations that support our findings

Technologies we use

snowflake - data intelligence technologies used by growexx

Snowflake

Amazon Web Services

tebleau - data intelligence technologies used by growexx

Tableau

powerbi - data intelligence technologies used by growexx

Power BI

apache airflow - data intelligence technologies used by growexx

Airflow

kubernetes - data intelligence technologies used by growexx

Kubernetes

jenkins - data intelligence technologies used by growexx

Jenkins

azure - data intelligence technologies used by growexx

Azure

Our Works

Data Intelligence case studies

FAQs

Data analytics is essential because it helps businesses optimize their performances. Implementing data analytics into the business model means businesses can help reduce costs by identifying even more efficient ways of doing business. A company can use data analytics to make better business decisions and help identify and analyze customer trends and feedback, which may lead to new—and better—products and/or services.

Data analytics is broken down into four types. Descriptive analytics explains what has happened over in the past. Diagnostic analytics focuses more on why certain things happened the way they happen. Predictive analytics moves to what is likely going to happen in the near term. And prescriptive analytics suggests what further course of action must be.

A few popular data analytics tools include –

  • R and Python
  • Microsoft Excel
  • Tableau
  • RapidMiner
  • KNIME
  • Power BI
  • Apache Spark

Business intelligence (BI) and two of its subsets—business analytics and data analytics—are all data management solutions used to analyze historical and contemporary data and create actionable insights for bsuinesses.

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