Re-Shape your business with
big data analytics

Leverage big data analytics as your newest
competitive advantage

The volume of terabytes of data being continuously generated and stored in data centres and databases of companies is increasing rapidly by the second. Across industries, these data sets become more difficult to manage when they grow with great velocity over time. The bulk of the information is unstructured or semi structured and is extracted from text files, videos, audio, and a variety of other sources and software formats. To manage these massive data sets more easily, businesses need to choose big data analytics.
Managing “integrated” big data guarantees more decision-making confidence and offers improved insights. Big data analytics supports better and quicker decision-making, modelling and outcome prediction, besides improved business intelligence.

Unlock more organisational value with big data insights from PredictiVu

PredictiVu’s big data analytics lets businesses drive transformation to a data driven culture. Using statistical analysis techniques, like clustering and regression, businesses can simplify the complex process of segregating relevant information from market trends, hidden data, unknown correlations, historical behaviour patterns, and customer preferences.
Businesses collect data from a range of sources, both organised and unstructured. Data warehouses store some of the data so that business intelligence tools and solutions may quickly access it. Excessive diversity in unstructured data may require metadata assignment and storage in a data lake. To produce correct results for analytical queries, data must be appropriately structured after it has been gathered and stored.

Our approach to big data analytics

PredictiVu employs stream processing for short batches of data and batch processing for large data blocks. So, once the data is ready, advanced analytics processes can convert big data into big insights. PredictiVu works with several such use cases to extract more value from organisational data, to drive predictive analytics and forecasting as key components of big data initiatives for clients. This will help businesses understand the future buying behaviour of customers and what customers want from them. This is crucial for companies to make timely strategic decisions for customer retention.




Data Integration
Using big data integration tools, businesses with massive data sets merge data coming from many sources and software formats before giving users a unified and translated view of the gathered data.
Data Warehousing
A Big Data ecosystem includes data warehouses and data lakes. A data warehouse with a clever architecture can grow to accommodate your demands both today and in the future.
Data Visualisation & BI
Using data visualisation techniques, raw data can transform into meaningful information. Further translations into the language of the corporate world are provided by business intelligence (BI).
Software Solutions
This involves designing specialised big data applications to investigate, examine, and handle a variety of data based on customer requirements. These solutions work with streaming, conventional, and atypical data types.

Benefits of big data analytics

Innovation: Big data analytics is a key driver of innovation for businesses.

Cost savings: For storing vast amounts of data, big data technologies like cloud-based analytics can dramatically lower expenses.

New goods and services: Big data analytics gives more businesses the chance to create cutting-edge new products and services in response to the shifting demands of their customers.

95% of firms identify managing unstructured data as a challenge for their industry.

At least one Big Data workload is being run in the cloud by 45% of businesses globally.


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