At the heart of every business decision making is data, no matter the nature or size of the organization. We are increasingly living in a data-driven and outcomes oriented environment. Business organizations see data more as a tool to distinguish themselves from market-with decisions based on facts, historical trends and statistical data.
Organizations that understand the significance of data collection are capitalizing on it
With so much data produced every day, businesses must be able to separate wheat from the chaff and arrive at meaningful business insights, so that they can make informed decisions. When used correctly, data can unlock new business opportunities, scale business new heights and give the much needed competitive edge to stay ahead of the competitive curve. Data should be the fuel for quick and confident business decisions. Unfortunately, data teams spend a majority of their time managing data before they can get on with analysis. 80% of IT teams time is spend on
80% of IT team’s time is spent on collecting large volumes of structured and unstructured data in particular, segregating it and discovering the patterns and deriving meaningful business insights from it, which are all tasks a conventional software meant for managing structured data simply can’t do.
Organizations have been witnessing an increase in volume, velocity and veracity of data. As a result managing huge data and getting meaningful business insights is becoming more complex and difficult. Many companies face these challenges because IT departments may have deployed COTS software tools to manage the data. Data challenges have evolved. Conventional, on-premise software tools are simply unable to provide the agility, scale and efficiency that today’s businesses and analytics use cases demand.
How confident are you about successfully using traditional processing systems for your data management needs? Despite 60-80% of organizations experimenting with new big data technologies, only a few have been able to successfully extract value sustainably.
Time and time again, we see companies invest time creating projects involving huge amounts of data, only to fail because traditional software systems fail to support big data processing. Part of the reason is that the data types including unstructured and semi-structured that constitutes the big data doesn’t easily fit into traditional DW that are largely centered around relational databases. There are many reasons why a conventional data warehouse is not ideal for processing big data sets. Because a typical data warehouse is built for processing structured data sets and will not be able to handle the huge processing demands as required by big data sets. That’s why organizations need to invest in big data analytics solutions which utilize specialized software tools and applications for big data analytics.
Did you know that organizations that use big data analytics are more likely to make accurate business decisions within the decision window?
Data analytics involves analyzation of huge data sets in an effort to derive insights and patterns. In other words big data analytics process involves extracting meaningful insights by way of analyzing multiple types of big data sets.
The need for big data analytics
Fast decision making is increasingly becoming a business imperative. Like never before organizations are under pressure to make quick decisions to keep up pace with the fast changing market conditions. Fast decision making is becoming a critical factor in business’s success.
Enterprises gather information from a variety of sources including internal and external. That makes it possible for a business to see where improvements are necessary. Data provides enough insights for organizations to identify the gaps and bridge the potential gap. As data becomes more accessible to everyone, it can help all the stakeholders within the company in increasing productivity and enhancing decision making. It comes as no surprise that big data analytics has become an inevitable tool for organizations seeking to accelerate decision making.
IT organizations from small, mid-market to large enterprises can achieve competitive advantage and enhance business performance by leveraging big data analytics.
Did you know that when it comes to Big Data Analytics, Prime has in-depth domain knowledge in Big Data Analytics and Business Intelligence is backed by a network of global delivery centers?
That’s right– Prime provides industry-leading experts to ensure your business intelligence needs are met in three main service areas:
- Data Acquisition
- Data Mining/OLAP
- Data Management and Architecture
Why not take a moment to explore Prime’s services ranging from Data Analytics to Business Intelligence solutions.