Big data analytics enables organizations in Uganda to analyze a mix of structured, semi-structured and unstructured data in search of valuable business information and insights. Big data is now a reality: The volume, variety and velocity of data coming into your organization continue to reach unprecedented levels. This phenomenal growth means that not only must you understand big data in order to decipher the information that truly counts, but you also must understand the possibilities of big data analytics in Ugandda. Since we are experiencing a paradigm shift where companies continue to receive large amount of different varieties of data coming into their systems the need for simplified yet reliable applications to manage, analyze, and provide insight on this data grows by the minute. Ar LMA Technologies we are right at the center of this revolutions and we provide both pre-built and custom solutions to enable organizations efficiently manage their big data needs.

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What is Big Data Analytics in Uganda?

Big data analytics is the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions. With big data analytics, data scientists and others can analyze huge volumes of data that conventional analytics and business intelligence solutions can't touch. Consider that your organization could accumulate (if it hasn't already) billions of rows of data with hundreds of millions of data combinations in multiple data stores and abundant formats. High-performance analytics is necessary to process that much data in order to figure out what's important and what is not.

For years SAS customers have evolved their analytics methods from a reactive view into a proactive approach using predictive and prescriptive analytics. Both reactive and proactive approaches are used by organizations, but let's look closely at what is best for your organization and task at hand.

Why is Big Data Analytics Important in Uganda?

Why collect and store terabytes of data if you can not analyze it in full context? Or if you have to wait hours or days to get results? With new advances in computing technology, there's no need to avoid tackling even the most challenging business problems. For simpler and faster processing of only relevant data, you can use high-performance analytics. Using high-performance data mining, predictive analytics, text mining, forecasting and optimization on big data enables you to continuously drive innovation and make the best possible decisions. In addition, organizations are discovering that the unique properties of machine learning are ideally suited to addressing their fast-paced big data needs in new ways


Power BI
Microsoft Excel
Hadoop
Apache Spark
MemSQL
Apache Cassandra
Stata
SPSS